~ Orders of magnitude (length)
- ~ 20th century
- ~ Periodization
- ~ Planck_time
- + -
~ Time (Orders of magnitude)
- yoctosecond zeptosecond
- ~ Attosecond
- ~ Femtosecond
- ~ Picosecond
- ~ Nanosecond
- ~ Microsecond
- ~ Millisecond
- ~ Second
- + -
~ Minute
- ~ Utopia
- ~ List of freedom indices
- ~ Homeostasis
-
DirectionologyMilky Way and Andromeda galaxy are approaching each other with a speed of about 130 km/s, however the collision of these two galaxies will not occur for about 5 billion years (AstroFile). Another result I found was that our galaxy and neighbors are moving at 600 km/s in the direction of the constellation Hydra (Scientific American). Finally, I found that the Milky Way moves through space within the cluster of galaxies it is a member of, and this cluster in turn moves through space towards yet another larger cluster of galaxies off in the direction of the constellation Virgo. This speed is approximately 300 km/s (Ask the Space Scientist). Therefore, the speed of the Milky Way galaxy is not a single number, its value is relative to the speed of other objects.
- ~ hypertextbook.com > Facts > 1999 > PatriciaKong
- ~ brainstuffshow.com > Blog > Good-question-how-fast-are-you-moving-through-the-universe-right-now
Survey effects of scale motions with pioneer and voyager type robots, effects of gravity over distence. Probes targeted towards and opposition, to measure velocities and resistences.Andromeda_GalaxyVirgo_superclusterSince the late 1980s it has been apparent that not only the Local Group, but all matter out to a distance of at least 50 Mpc is experiencing a bulk flow on the order of 600 km/sec in the direction of the Norma cluster (Abell 3627).[10] Lynden-Bell et al. (1988) dubbed the cause of this "The Great Attractor." While astronomers are confident of the velocity of the LS, which has been measured against the Cosmic Microwave Background (CMB), the nature of what is causing it remains poorly understood.
-
- ~ Intersectionality
- ~ Conflict
- ~ List of ongoing armed conflicts
- ~ War
- ~ Dystopia
- ~ 21st century
- ~ List of terrorist incidents, 2015
- ~
M
- ~ 20th century
- ~ Periodization
- ~ Planck_time
- ~ Time (Orders of magnitude)
- yoctosecond zeptosecond
- ~ Attosecond
- ~ Femtosecond
- ~ Picosecond
- ~ Nanosecond
- ~ Microsecond
- ~ Millisecond
- ~ Second
- + -
~ Minute
- ~ Utopia
- ~ List of freedom indices
- ~ Homeostasis
-
DirectionologyMilky Way and Andromeda galaxy are approaching each other with a speed of about 130 km/s, however the collision of these two galaxies will not occur for about 5 billion years (AstroFile). Another result I found was that our galaxy and neighbors are moving at 600 km/s in the direction of the constellation Hydra (Scientific American). Finally, I found that the Milky Way moves through space within the cluster of galaxies it is a member of, and this cluster in turn moves through space towards yet another larger cluster of galaxies off in the direction of the constellation Virgo. This speed is approximately 300 km/s (Ask the Space Scientist). Therefore, the speed of the Milky Way galaxy is not a single number, its value is relative to the speed of other objects.Survey effects of scale motions with pioneer and voyager type robots, effects of gravity over distence. Probes targeted towards and opposition, to measure velocities and resistences.Andromeda_GalaxyVirgo_supercluster
Since the late 1980s it has been apparent that not only the Local Group, but all matter out to a distance of at least 50 Mpc is experiencing a bulk flow on the order of 600 km/sec in the direction of the Norma cluster (Abell 3627).[10] Lynden-Bell et al. (1988) dubbed the cause of this "The Great Attractor." While astronomers are confident of the velocity of the LS, which has been measured against the Cosmic Microwave Background (CMB), the nature of what is causing it remains poorly understood.
-
- ~ Intersectionality
- ~ Conflict
- ~ Dystopia
- ~ 21st century
- ~ Minute
- ~ Utopia
- ~ List of freedom indices
- + -
+ - i
- ~ Effect size
- + -
Form may also refer to:
- Form, a shallow depression or flattened nest of grass used by a hare
- Form (document), a document (printed or electronic) with spaces in which to write or enter data
- Form (education), a class, set or group of students
- Form (exercise), a proper way of performing an exercise
- Form (horse racing), a record of a racehorse's performance, or similarly for an athlete
- Form, a criminal record
- Form, a font designed by Aldo Novarese (1966)
- Form (religion), an academic term for prescriptions or norms on religious practice
- Musical form, a generic type of composition or the structure of a particular piece
- FORM, an American architecture magazine
- + -
Biology:
- Form (botany), a formal taxon at a rank lower than species
- Form (zoology), informal taxa used sometimes in zoology
- + -
Computing:
- Form (web), a document form used on a web page to, typically, submit user data to a server
- Form (programming), a component-based representation of a GUI window
- FORM (symbolic manipulation system), a program for symbolic computations
- Form (computer virus), the most common computer virus of the 1990s
- Oracle Forms, a Rapid Application Development environment for developing database applications
- Windows Forms
- XForms, an XML format for the specification of user interfaces, specifically web forms
- Trapcode Form, a motion graphic editing plug-in from Red Giant Software
- + -
Martial arts:
- Kata (型 or 形), the detailed pattern of defence-and-attack
- Taeguk (Taekwondo) (형), the "forms" used to create a foundation for the teaching of Taekwondo
- Taolu (套路), forms used in Chinese martial arts and sport wushu
- + -
Mathematics:
Algebraic form (homogeneous polynomial), which generalises quadratic forms to degrees 3 and more, also known as quantics or simply forms
Bilinear form, on a vector space V over a field F is a mapping V × V → F that is linear in both arguments
Differential form, a concept from differential topology that combines multi linear forms and smooth functions
Indeterminate form, an algebraic expression that cannot be used to evaluate a limit
Modular form, a (complex) analytic function on the upper half plane satisfying a certain kind of functional equation and growth condition
Multilinear form, which generalises bilinear forms to mappings VN → F
Quadratic form, a homogeneous polynomial of degree two in a number of variables
- + -
Philosophy:
Substantial form
Theory of Forms
Value-form, an approach to understanding the origins of commodity trade and the formation of markets.
- + -
See also
- Formwork, a mould used for concrete construction
- Isoform, several different forms of the same protein
- Sixth form, an English term for the final two years of secondary school
- The Forms (band), an American indie rock band
- Formation (disambiguation)
- Formula (disambiguation)
- Conformity (disambiguation)
- Deformation (disambiguation)
- Inform (disambiguation)
- Reform (disambiguation)
- All pages beginning with "Form"
- All pages with titles containing "Form"
- + -
Form may also refer to:
- Form refers to the shape, visual appearance, or configuration of an object.
- ~ shape
- ~ visual appearance
- ~ configuration
- ~ hare
- ~ Form (document)
- ~ Form (education)
- ~ Form (exercise)
- ~ Form (horse racing)
- ~ criminal record
- ~ Aldo Novarese
- ~ Form (religion)
- ~ Musical form
- ~ FORM
- ~ Form (botany)
- ~ Form (zoology)
- ~ Form (web)
- ~ Form (programming)
- ~ FORM (symbolic manipulation system)
- ~ Form (computer virus)
- ~ Oracle Forms
- ~ Windows Forms
- ~ XForms
- ~ Red Giant Software
- ~ Kata
- ~ Taeguk (Taekwondo)
- ~ Taolu
- ~ homogeneous polynomial
- ~ Bilinear form
- ~ Differential form
- ~ Indeterminate form
- ~ Modular form
- ~ Multilinear form
- ~ Quadratic form
- ~ Substantial form
- ~ Theory of Forms
- ~ Value-form
- ~ edit
- ~ Formwork
- ~ Isoform
- ~ Sixth form
- ~ The Forms (band)
- ~ Formation (disambiguation)
- ~ Formula (disambiguation)
- ~ Conformity (disambiguation)
- ~ Deformation (disambiguation)
- ~ Inform (disambiguation)
- ~ Reform (disambiguation)
- ~ All pages beginning with "Form"
- ~ All pages with titles containing "Form"
+ - i
- ~ result
- ~ List of effects
- ~ causality
- ~ Drug effect
- ~ Therapeutic effect
- ~ Adverse effect
- ~ dose-response curve
- ~ Special effect
- ~ Sound effect
- ~ Effects unit
- ~ Effects pedal
- ~ Visual effects
- ~ personal property
- ~ All pages beginning with "Effect"
- ~ All pages with titles containing "Effect"
- ~ Affect (disambiguation)
- ~ Effectiveness (disambiguation)
- ~ Efficacy
- ~ Pragmatism
Mission:
- + -
Deep Green (DG)
Program Manager: Dr. Todd Hughes (AEO)- ~
http://www.darpa.mil/ipto/programs/dg/dg.asp
~
http://www.defenseindustrydaily.com/files/PUB_BAA_DARPA_07-56_Deep_Green.pdf
The Deep Green concept is an innovative approach to using simulation to support ongoing military operations while they are being conducted. The basic approach is to maintain a state-space graph of possible future states. Software agents use information on the trajectory of the ongoing operation, vice a priori staff estimates as to how the battle might unfold, as well as simulation technologies, to assess the likelihood of reaching some set of possible future states. The likelihood, utility, and flexibility of possible future nodes in the state space graph are computed and evaluated to focus the planning efforts. This notion is called anticipatory planning and involves the generation of options (either manual or semi-automated) ahead of "real time," before the options are needed. In addition, the Deep Green concept provides mechanisms for adaptive execution, which can be described as "late binding," or choosing a branch in the state space graph at the last moment to maintain flexibility. By using information acquired from the ongoing operation, rather than assumptions made during the planning phase, commanders and staffs can make more informed choices and focus on building options for futures that are becoming more likely.
Deep Learning
- ~
http://www.darpa.mil/ipto/programs/deep/deep.asp
+ -
Vision:
-
The Deep Learning program will discover and instantiate in a learning machine (Deep Learning System) a single set of methods that, when applied repeatedly across multiple layers of the machine, yield more useful representations of audio/visual, sensor, and language information, using less labeled data more efficiently than any existing technologies.
Mission:
-
The Deep Learning program aims to revolutionize machine learning by creating a new class of learning machines that overcome the computational limitations of current "shallow" learning machines. This will be done by building machines that can use many layers of processing in a manner that is, at least superficially, similar to that used by biological brains. The Deep Learning program will develop a Core Deep Learner that creates rich encodings of input data by using the same set of algorithms across multiple layers and will demonstrate that the Core Deep Learner can be applied successfully, and with little or no modification, to processing data from different modalities and application areas.
-
Bootstrapped Learning (BL)
-
Program Manager:
+ -
Mission:
-
The Bootstrapped Learning program seeks to make instructable computing a reality. The "electronic student" will learn from a human teacher who uses spoken language, gestures, demonstration, and many other methods one would find in a human mentored relationship. Furthermore, it will build upon learned concepts and apply that knowledge across different fields of study.
Embedding BL technology in computing systems will eliminate the need for trained programmers in many practical settings, significantly accelerating human-machine instruction, and making possible on-the-fly upgrades by domain experts rather than computer experts. Target applications include a variety of field-trainable military systems, such as human-instructable unmanned aerial vehicles. However, BL technology is being developed and tested against a portfolio of training tasks across very diverse domains, thus it can be applied to any programmable, automated system. As such systems have become ubiquitous, and their operation inaccessible to the layperson, there is also the strong prospect of societal adoption and benefit.
-
Vision:
-
Deep Green is a next-generation, commander-centered battle command and decision support technology that interleaves anticipatory planning with adaptive execution to help the commander think ahead, identify when a plan is going awry, and prepare options - before they are needed.
Approach:
-
Effective battlespace representations for Deep Green must enable practical and tractable reasoning by software agents. In particular, the generation of a state-space representation from current operational data is particularly challenging. Deep Green must be able to use data and information fusion to dynamically create and update representations of the current battle space. Deep Green will then use these representations to predict the "trajectory" of the operation and inform the commander of impending decision points, parts of the plan that need additional options generated, and parts of the plan that are no longer feasible.
Deep Green will involve the use of software agents to analyze the current operation against the plan and to look far ahead in time for the commander to create possible courses of action. These "execution monitors" must be capable of reasoning over the state space to evaluate the actions of the various participants, evaluate the utility and likelihood of actions, and prune the state space representation where possible. Most of this kind of agent technology has proven effective in constrained problem spaces, but must be hardened and scaled to support a real battlespace.
Finally learning algorithms must be developed and enhanced to allow Deep Green to become a better predictor over time. Technologies such as linguistic geometry and episodic memory must be employed to create robust learning algorithms suited for battlefield use. Many of these technologies must be extended to encompass the intractable nature of the modern battlefield as they have been demonstrated in more "well behaved" domains. The domain for Deep Blue, the game of chess, for instance, is well known, the interactions are unambiguously defined, the consequences of any single action are deterministic, etc.
The basic system architecture is comprised of the Commander's Associate (with three sub-components, the Sketch to Plan, Automated Options Generation, and the Sketch to Decide), SimPath, and Crystal Ball, as shown in the figure below.
Sketch to Plan:
-
The Commander's Associate has two major sub-components, Sketch to Plan and Sketch to Decide. Commander's Associate will automatically convert the commander's hand-drawn sketch with accompanying speech of his intent into a Course of Action (COA) at the brigade level. The Commander's Associate must facilitate option generation, "what-if" drills, and rapid decision making. In addition, the Commander's Associate will present information to the commander in a way that aids in battlefield visualization and cognition.
+ - Yellow Pilot
- + -
HSCB
-
CAPABILITIES
-
HSCB programs are organized into four capabilities, each set feeding into the next and forming a cycle.
+ --
Understand
Understand sociocultural parameters of operational environment.
-
Capabilities to support thorough perception and comprehension, grounded in social and behavioral science, of the sociocultural features and dynamics in an operational environment.
The cycle begins with the need to frame the sociocultural structure and dynamics of behavior in a given operational context. To understand at this level means bringing sociocultural theory and concepts to bear to identify the sociocultural features of the terrain that are important to monitor. Understanding is not a single event, and users may constantly need to adapt the initially-applied theories, concepts, and consequent features based on the results of detecting, forecasting, and mitigation. This then initiates a new cycle. This step spans all levels - tactical, operational, and strategic. It requires applied social and behavioral science theory, access to baseline sociocultural data for any given region, descriptive models, and linguistic and sociocultural training.
-
Detect
Detect valid sociocultural behavior signals from noise.
-
Capabilities to discover, distinguish, and locate operationally relevant sociocultural signatures through the collection, processing, and analysis of sociocultural behavior data.
Once the defining features of the sociocultural setting are understood, the next steps are to develop a persistent capability to detect sociocultural behavior signals of interest amidst complexity and noise, and to harvest data for analysis. This entails capabilities for ISR in the area of sociocultural behavior (referred to here as a "social radar"), with particular focus on the challenges associated with open source data collection. It also requires robust systems for storing and managing that data, and tools enabling timely, dynamic analysis.
-
Forecast
Forecast behaviors in response to possible COAs.
-
Capabilities for tracking and forecasting change in entities and phenomena of interest along multiple dimensions (time, space, social networks, types of behavior, etc.) through persistent sensing and modeling of the environment.
Armed with historical and real-time data, users can take the next step: to forecast alternative plausible futures by extrapolating from the collected data. The goals are to identify the various paths that behaviors of interest could take, and to estimate the consequences of each for populations of interest. Among the most important needs in this step are large amounts of data, multidisciplinary theory, and hybrid modeling.
-
Mitigate
Mitigate behaviors and measure effects.
-
Capabilities to develop, prioritize, execute, and measure COAs grounded in the social and behavioral sciences.
The final step in the cycle is to develop and measure the effects of alternative COAs for achieving desired changes. This step builds on all the foregoing ones, and should assist in updating U.S. forces' understanding of the sociocultural behavior terrain, thus continuing the cycle. This step requires education in the use of models for robust decision making, strategic-level theory, integrated systems, decision space visualization, and agile data collection.
OTHER SOCIOCULTURAL PROGRAMS
Minerva
Strategic Multi-Layer Assessment (SMA)
National Science Foundation's Directorate for Social, Behavioral and Economic Sciences
Air Force Office of Scientific Research Collective Behavior and Socio-Cultural Modeling
Air Force Research Laboratory Human Effectiveness Directorate (RH)
- Anticipate and Influence Behavior Division
- National Operational Environment Model
U.S. Army Corps of Engineers (USACE)
- Army Geospatial Center (AGC)
- Measuring Progress in Conflict Environments (MPICE)
U.S. Army Research Institute for the Behavioral and Social Sciences (ARI) Learning and Operating in Culturally Unfamiliar Settings (LOCUS)
U.S. Army Research Laboratory (ARL)
- Human Research and Engineering Directorate
- Network Science Collaborative Technology Alliance
U.S. Army Training and Doctrine Command (TRADOC)
- Cultural Knowledge Consortium (CKC)
- Human Terrain System
Office of Naval Research (ONR) Affordable Human Behavior Modeling (AHBM)
-
Understand
- Syria
~ https://www.facebook.com/permalink.php?story_fbid=1030388917000681&id=658176844221892 + -
In June 2014, ISIL had at least 4,000 fighters in Iraq, and the CIA estimated in September 2014 that it had 20,000–31,500 fighters in Iraq and Syria. The Syrian Observatory for Human Rights estimates that the force numbers around 80,000–100,000 total (up to 50,000 in Syria and 30,000 in Iraq).-
Military activity of ISIL - Wikipedia, the free encyclopedia
-
- + - Somalia
- + - Nigeria
- + - Bangladesh
Process
-
-
+ - ~ 21st century
- ~ List of terrorist incidents, 2015
- ~
M
- ~ 20th century
- ~ Periodization
- ~ Planck_time
- ~ Time (Orders of magnitude)
- yoctosecond zeptosecond
- ~ Attosecond
- ~ Femtosecond
- ~ Picosecond
- ~ Nanosecond
- ~ Microsecond
- ~ Millisecond
- ~ Second
- + -
~ Minute
- ~ Utopia
- ~ List of freedom indices
- ~ Homeostasis
-
DirectionologyMilky Way and Andromeda galaxy are approaching each other with a speed of about 130 km/s, however the collision of these two galaxies will not occur for about 5 billion years (AstroFile). Another result I found was that our galaxy and neighbors are moving at 600 km/s in the direction of the constellation Hydra (Scientific American). Finally, I found that the Milky Way moves through space within the cluster of galaxies it is a member of, and this cluster in turn moves through space towards yet another larger cluster of galaxies off in the direction of the constellation Virgo. This speed is approximately 300 km/s (Ask the Space Scientist). Therefore, the speed of the Milky Way galaxy is not a single number, its value is relative to the speed of other objects.Survey effects of scale motions with pioneer and voyager type robots, effects of gravity over distence. Probes targeted towards and opposition, to measure velocities and resistences.Andromeda_GalaxyVirgo_supercluster
Since the late 1980s it has been apparent that not only the Local Group, but all matter out to a distance of at least 50 Mpc is experiencing a bulk flow on the order of 600 km/sec in the direction of the Norma cluster (Abell 3627).[10] Lynden-Bell et al. (1988) dubbed the cause of this "The Great Attractor." While astronomers are confident of the velocity of the LS, which has been measured against the Cosmic Microwave Background (CMB), the nature of what is causing it remains poorly understood.
-
- ~ Intersectionality
- ~ Conflict
- ~ Dystopia
- ~ 21st century
- ~ Minute
- ~ Utopia
- ~ List of freedom indices
-
+ - i
- ~ Effect size
- + -
Form may also refer to:
- Form, a shallow depression or flattened nest of grass used by a hare
- Form (document), a document (printed or electronic) with spaces in which to write or enter data
- Form (education), a class, set or group of students
- Form (exercise), a proper way of performing an exercise
- Form (horse racing), a record of a racehorse's performance, or similarly for an athlete
- Form, a criminal record
- Form, a font designed by Aldo Novarese (1966)
- Form (religion), an academic term for prescriptions or norms on religious practice
- Musical form, a generic type of composition or the structure of a particular piece
- FORM, an American architecture magazine
- + -
Biology:
- Form (botany), a formal taxon at a rank lower than species
- Form (zoology), informal taxa used sometimes in zoology
- + -
Computing:
- Form (web), a document form used on a web page to, typically, submit user data to a server
- Form (programming), a component-based representation of a GUI window
- FORM (symbolic manipulation system), a program for symbolic computations
- Form (computer virus), the most common computer virus of the 1990s
- Oracle Forms, a Rapid Application Development environment for developing database applications
- Windows Forms
- XForms, an XML format for the specification of user interfaces, specifically web forms
- Trapcode Form, a motion graphic editing plug-in from Red Giant Software
- + -
Martial arts:
- Kata (型 or 形), the detailed pattern of defence-and-attack
- Taeguk (Taekwondo) (형), the "forms" used to create a foundation for the teaching of Taekwondo
- Taolu (套路), forms used in Chinese martial arts and sport wushu
- + -
Mathematics:
Algebraic form (homogeneous polynomial), which generalises quadratic forms to degrees 3 and more, also known as quantics or simply forms
Bilinear form, on a vector space V over a field F is a mapping V × V → F that is linear in both arguments
Differential form, a concept from differential topology that combines multi linear forms and smooth functions
Indeterminate form, an algebraic expression that cannot be used to evaluate a limit
Modular form, a (complex) analytic function on the upper half plane satisfying a certain kind of functional equation and growth condition
Multilinear form, which generalises bilinear forms to mappings VN → F
Quadratic form, a homogeneous polynomial of degree two in a number of variables
- + -
Philosophy:
Substantial form
Theory of Forms
Value-form, an approach to understanding the origins of commodity trade and the formation of markets.
- + -
See also
- Formwork, a mould used for concrete construction
- Isoform, several different forms of the same protein
- Sixth form, an English term for the final two years of secondary school
- The Forms (band), an American indie rock band
- Formation (disambiguation)
- Formula (disambiguation)
- Conformity (disambiguation)
- Deformation (disambiguation)
- Inform (disambiguation)
- Reform (disambiguation)
- All pages beginning with "Form"
- All pages with titles containing "Form"
- + -
Form may also refer to:
- Form refers to the shape, visual appearance, or configuration of an object.
- ~ shape
- ~ visual appearance
- ~ configuration
- ~ hare
- ~ Form (document)
- ~ Form (education)
- ~ Form (exercise)
- ~ Form (horse racing)
- ~ criminal record
- ~ Aldo Novarese
- ~ Form (religion)
- ~ Musical form
- ~ FORM
- ~ Form (botany)
- ~ Form (zoology)
- ~ Form (web)
- ~ Form (programming)
- ~ FORM (symbolic manipulation system)
- ~ Form (computer virus)
- ~ Oracle Forms
- ~ Windows Forms
- ~ XForms
- ~ Red Giant Software
- ~ Kata
- ~ Taeguk (Taekwondo)
- ~ Taolu
- ~ homogeneous polynomial
- ~ Bilinear form
- ~ Differential form
- ~ Indeterminate form
- ~ Modular form
- ~ Multilinear form
- ~ Quadratic form
- ~ Substantial form
- ~ Theory of Forms
- ~ Value-form
- ~ edit
- ~ Formwork
- ~ Isoform
- ~ Sixth form
- ~ The Forms (band)
- ~ Formation (disambiguation)
- ~ Formula (disambiguation)
- ~ Conformity (disambiguation)
- ~ Deformation (disambiguation)
- ~ Inform (disambiguation)
- ~ Reform (disambiguation)
- ~ All pages beginning with "Form"
- ~ All pages with titles containing "Form"
+ - i
- ~ result
- ~ List of effects
- ~ causality
- ~ Drug effect
- ~ Therapeutic effect
- ~ Adverse effect
- ~ dose-response curve
- ~ Special effect
- ~ Sound effect
- ~ Effects unit
- ~ Effects pedal
- ~ Visual effects
- ~ personal property
- ~ All pages beginning with "Effect"
- ~ All pages with titles containing "Effect"
- ~ Affect (disambiguation)
- ~ Effectiveness (disambiguation)
- ~ Efficacy
- ~ Pragmatism
Mission:
- + -
Deep Green (DG)
Program Manager: Dr. Todd Hughes (AEO)- ~
http://www.darpa.mil/ipto/programs/dg/dg.asp
~
http://www.defenseindustrydaily.com/files/PUB_BAA_DARPA_07-56_Deep_Green.pdf
The Deep Green concept is an innovative approach to using simulation to support ongoing military operations while they are being conducted. The basic approach is to maintain a state-space graph of possible future states. Software agents use information on the trajectory of the ongoing operation, vice a priori staff estimates as to how the battle might unfold, as well as simulation technologies, to assess the likelihood of reaching some set of possible future states. The likelihood, utility, and flexibility of possible future nodes in the state space graph are computed and evaluated to focus the planning efforts. This notion is called anticipatory planning and involves the generation of options (either manual or semi-automated) ahead of "real time," before the options are needed. In addition, the Deep Green concept provides mechanisms for adaptive execution, which can be described as "late binding," or choosing a branch in the state space graph at the last moment to maintain flexibility. By using information acquired from the ongoing operation, rather than assumptions made during the planning phase, commanders and staffs can make more informed choices and focus on building options for futures that are becoming more likely.
Deep Learning
- ~
http://www.darpa.mil/ipto/programs/deep/deep.asp
+ -
Vision:
-
The Deep Learning program will discover and instantiate in a learning machine (Deep Learning System) a single set of methods that, when applied repeatedly across multiple layers of the machine, yield more useful representations of audio/visual, sensor, and language information, using less labeled data more efficiently than any existing technologies.
Mission:
-
The Deep Learning program aims to revolutionize machine learning by creating a new class of learning machines that overcome the computational limitations of current "shallow" learning machines. This will be done by building machines that can use many layers of processing in a manner that is, at least superficially, similar to that used by biological brains. The Deep Learning program will develop a Core Deep Learner that creates rich encodings of input data by using the same set of algorithms across multiple layers and will demonstrate that the Core Deep Learner can be applied successfully, and with little or no modification, to processing data from different modalities and application areas.
-
Bootstrapped Learning (BL)
-
Program Manager:
+ -
Mission:
-
The Bootstrapped Learning program seeks to make instructable computing a reality. The "electronic student" will learn from a human teacher who uses spoken language, gestures, demonstration, and many other methods one would find in a human mentored relationship. Furthermore, it will build upon learned concepts and apply that knowledge across different fields of study.
Embedding BL technology in computing systems will eliminate the need for trained programmers in many practical settings, significantly accelerating human-machine instruction, and making possible on-the-fly upgrades by domain experts rather than computer experts. Target applications include a variety of field-trainable military systems, such as human-instructable unmanned aerial vehicles. However, BL technology is being developed and tested against a portfolio of training tasks across very diverse domains, thus it can be applied to any programmable, automated system. As such systems have become ubiquitous, and their operation inaccessible to the layperson, there is also the strong prospect of societal adoption and benefit.
-
Vision:
-
Deep Green is a next-generation, commander-centered battle command and decision support technology that interleaves anticipatory planning with adaptive execution to help the commander think ahead, identify when a plan is going awry, and prepare options - before they are needed.
Approach:
-
Effective battlespace representations for Deep Green must enable practical and tractable reasoning by software agents. In particular, the generation of a state-space representation from current operational data is particularly challenging. Deep Green must be able to use data and information fusion to dynamically create and update representations of the current battle space. Deep Green will then use these representations to predict the "trajectory" of the operation and inform the commander of impending decision points, parts of the plan that need additional options generated, and parts of the plan that are no longer feasible.
Deep Green will involve the use of software agents to analyze the current operation against the plan and to look far ahead in time for the commander to create possible courses of action. These "execution monitors" must be capable of reasoning over the state space to evaluate the actions of the various participants, evaluate the utility and likelihood of actions, and prune the state space representation where possible. Most of this kind of agent technology has proven effective in constrained problem spaces, but must be hardened and scaled to support a real battlespace.
Finally learning algorithms must be developed and enhanced to allow Deep Green to become a better predictor over time. Technologies such as linguistic geometry and episodic memory must be employed to create robust learning algorithms suited for battlefield use. Many of these technologies must be extended to encompass the intractable nature of the modern battlefield as they have been demonstrated in more "well behaved" domains. The domain for Deep Blue, the game of chess, for instance, is well known, the interactions are unambiguously defined, the consequences of any single action are deterministic, etc.
The basic system architecture is comprised of the Commander's Associate (with three sub-components, the Sketch to Plan, Automated Options Generation, and the Sketch to Decide), SimPath, and Crystal Ball, as shown in the figure below.
Sketch to Plan:
-
The Commander's Associate has two major sub-components, Sketch to Plan and Sketch to Decide. Commander's Associate will automatically convert the commander's hand-drawn sketch with accompanying speech of his intent into a Course of Action (COA) at the brigade level. The Commander's Associate must facilitate option generation, "what-if" drills, and rapid decision making. In addition, the Commander's Associate will present information to the commander in a way that aids in battlefield visualization and cognition.
+ - Yellow Pilot
- + -
HSCB
-
CAPABILITIES
-
HSCB programs are organized into four capabilities, each set feeding into the next and forming a cycle.
+ --
Understand
Understand sociocultural parameters of operational environment.
-
Capabilities to support thorough perception and comprehension, grounded in social and behavioral science, of the sociocultural features and dynamics in an operational environment.
The cycle begins with the need to frame the sociocultural structure and dynamics of behavior in a given operational context. To understand at this level means bringing sociocultural theory and concepts to bear to identify the sociocultural features of the terrain that are important to monitor. Understanding is not a single event, and users may constantly need to adapt the initially-applied theories, concepts, and consequent features based on the results of detecting, forecasting, and mitigation. This then initiates a new cycle. This step spans all levels - tactical, operational, and strategic. It requires applied social and behavioral science theory, access to baseline sociocultural data for any given region, descriptive models, and linguistic and sociocultural training.
-
Detect
Detect valid sociocultural behavior signals from noise.
-
Capabilities to discover, distinguish, and locate operationally relevant sociocultural signatures through the collection, processing, and analysis of sociocultural behavior data.
Once the defining features of the sociocultural setting are understood, the next steps are to develop a persistent capability to detect sociocultural behavior signals of interest amidst complexity and noise, and to harvest data for analysis. This entails capabilities for ISR in the area of sociocultural behavior (referred to here as a "social radar"), with particular focus on the challenges associated with open source data collection. It also requires robust systems for storing and managing that data, and tools enabling timely, dynamic analysis.
-
Forecast
Forecast behaviors in response to possible COAs.
-
Capabilities for tracking and forecasting change in entities and phenomena of interest along multiple dimensions (time, space, social networks, types of behavior, etc.) through persistent sensing and modeling of the environment.
Armed with historical and real-time data, users can take the next step: to forecast alternative plausible futures by extrapolating from the collected data. The goals are to identify the various paths that behaviors of interest could take, and to estimate the consequences of each for populations of interest. Among the most important needs in this step are large amounts of data, multidisciplinary theory, and hybrid modeling.
-
Mitigate
Mitigate behaviors and measure effects.
-
Capabilities to develop, prioritize, execute, and measure COAs grounded in the social and behavioral sciences.
The final step in the cycle is to develop and measure the effects of alternative COAs for achieving desired changes. This step builds on all the foregoing ones, and should assist in updating U.S. forces' understanding of the sociocultural behavior terrain, thus continuing the cycle. This step requires education in the use of models for robust decision making, strategic-level theory, integrated systems, decision space visualization, and agile data collection.
OTHER SOCIOCULTURAL PROGRAMS
Minerva
Strategic Multi-Layer Assessment (SMA)
National Science Foundation's Directorate for Social, Behavioral and Economic Sciences
Air Force Office of Scientific Research Collective Behavior and Socio-Cultural Modeling
Air Force Research Laboratory Human Effectiveness Directorate (RH)
- Anticipate and Influence Behavior Division
- National Operational Environment Model
U.S. Army Corps of Engineers (USACE)
- Army Geospatial Center (AGC)
- Measuring Progress in Conflict Environments (MPICE)
U.S. Army Research Institute for the Behavioral and Social Sciences (ARI) Learning and Operating in Culturally Unfamiliar Settings (LOCUS)
U.S. Army Research Laboratory (ARL)
- Human Research and Engineering Directorate
- Network Science Collaborative Technology Alliance
U.S. Army Training and Doctrine Command (TRADOC)
- Cultural Knowledge Consortium (CKC)
- Human Terrain System
Office of Naval Research (ONR) Affordable Human Behavior Modeling (AHBM)
-
Understand
- Syria
~ https://www.facebook.com/permalink.php?story_fbid=1030388917000681&id=658176844221892 + -
In June 2014, ISIL had at least 4,000 fighters in Iraq, and the CIA estimated in September 2014 that it had 20,000–31,500 fighters in Iraq and Syria. The Syrian Observatory for Human Rights estimates that the force numbers around 80,000–100,000 total (up to 50,000 in Syria and 30,000 in Iraq).-
Military activity of ISIL - Wikipedia, the free encyclopedia
-
- + - Somalia
- + - Nigeria
- + - Bangladesh
Process
-
-
- + -
HSCB
Commander's Associate:
-
This component provides the commander the ability to generate quickly qualitative, coarse-grained COA sketches that the computer can interpret. Sketch to Plan will be multi-modal (both sketching and speech) and interactive. The computer will watch the sketch being drawn and listen for key words that indicate sequence, time, intent, etc. as the commander is creating the sketch. Sketch to Plan will induce both a plan and the commander's intent from the sketch and speech. The Sketch to Plan component must be imbued with enough domain knowledge that it knows what it doesn't know and can ask the user a small set of clarifying questions until it understands the sketch and can use it to initialize a combat model. Finally, the dialog generator helps Sketch to Plan understand the commander's option by formulating clarifying questions when necessary.
~ http://zephyr9673.tripod.com/class/I%20pilot%20two.html+ - i
- + - ~ 1 History
- + -
Strong AI
+ - i
- ~ artificial intelligence
- ~ intelligence
- ~ [1]
- ~ artificial intelligence
- ~ science fiction
- ~ futurists
- ~ [2]
- ~ [3]
- ~ Science fiction
- ~ consciousness
- ~ sentience
- ~ sapience
- ~ self-awareness
- ~ applied AI
- ~ [4]
- ~ [1]
- ~ [5]
- ~ problem solving
- ~ reasoning
Strong AI is artificial intelligence that matches or exceeds human intelligence — the intelligence of a machine that can successfully perform any intellectual task that a human being can.[1] It is a primary goal of artificial intelligence research and an important topic for science fiction writers and futurists. Strong AI is also referred to as "artificial general intelligence"[2] or as the ability to perform "general intelligent action".[3] Science fiction associates strong AI with such human traits as consciousness, sentience, sapience and self-awareness.
Some references emphasize a distinction between strong AI and "applied AI"[4] (also called "narrow AI"[1] or "weak AI"[5]): the use of software to study or accomplish specific problem solving or reasoning tasks that do not encompass (or in some cases are completely outside of) the full range of human cognitive abilities.
- ~ 7 Philosophy
- + - ~ 8 Prediction
- + - ~ 4 Tools
- + -
Contents
- + -
1 History
-
Web Directories, Dictionaries and Encyclopedias
-
BotSpot
What's a Bot?
In short: A bot is a software tool for digging through data. You give a bot directions and it bring back answers. The word is short for robot of course, which is derived from the Czech word robota meaning work.
The idea of robots as humanoid machines was first introduced in Karel Capek's 1921 play "R.U.R.," where the playwright conceived Rossum's Universal Robots. Sci-fi writer Isaac Asimov made them famous, beginning with his story I, Robot (1950) and continuing through a string of books known as the Robot Series (see the Isaac Asimov FAQ - for more details including "The Three Laws of Robotics"). - Easily Amused dot com Welcome o' yee of short attention span. Presented here is a collected list of web sites which I found amusing. Although my opinion will vary greatly from yours I hope that you find the majority of these sites at least worth the mouse click to access them.
- Wikipedia A.L.I.C.E. (Artificial Linguistic Internet Computer Entity) is an award-winning natural language processing chatterbot . a program that engages in a conversation with a human by applying some heuristical pattern matching rules to the human's input. It was inspired by Joseph Weizenbaum's classical ELIZA program but takes a quite different approach. It is one of the strongest programs of its type and has won the Loebner Prize three times (in 2000, 2001 and 2004).
- Agentland.com Alice (Artificial Linguistic Internet Computer Entity) is a natural language interface to a telerobot eye. Alice tries ironically to be a computer, so her replies may make some sense but in reality Alice is nothing more than a gigantic pattern-matching case-statement. Remarkably however this elaborate hoax has produced some of the most convincing natural conversations between computer andx humans yet observed.
- Open Directory Chatterbots: ALICE Computers: Artificial Intelligence: Natural Language: Chatterbots: ALICE
- AAAI AI Ethics Any sci-fi buff knows that when computers become self-aware, they ultimately destroy their creators. From 2001: A Space Odyssey to Terminator, the message is clear: The only good self-aware machine is an unplugged one. We may soon find out whether that's true. ... But what about HAL 9000 and the other fictional computers that have run amok?
- American Association for Artificial Intelligence A.I. topics -- Natural LanguageThe value to our society of being able to communicate with computers in everyday "natural" language cannot be overstated. Imagine asking your computer "Does this candidate have a good record on the environment?" or "When is the next televised National League baseball game?" Or being able to tell your PC "Please format my homework the way my English professor likes it".
- American Association for Artificial Intelligence A.I. topics -- The Turing TestAlan Turing proposed an operational test of intelligence as a replacement for the philosophical question, "Can machines think?" Variations of this test have been used to assess performance levels of many AI programs. A restricted adaptation of the Turing Test popularized by the Loebner Competition has been fun, although currently many AI scientists criticize the restricted version of the test because it does not provide insights into the mechanisms of thought.
- www.cs.um.edu.mt/~mros/nlp/ NLP Resource Page
- members.aol.com/lshauser/aiothers.html AI & Other Minds by Larry Hauser.
- www.faqs.org/faqs/ai-faq/general/part6/ Artificial Intelligence FAQ: Open Source AI Software "Chatbots: AI: There is a much maligned chatbot at the Warner Brothers page on the AI movie."
- Sitereview.org A.L.I.C.E is an "Artificial Linguistic Internet Computer Entity" capable of intelligent conversation. She will amaze you with her ability to come up with a relevant response to just about anything! If I didn't know better, I'd think she was human.
- You can become a Botmaster A chat robot is a program that attempts to simulate the conversation or "chat" of a human being. The Chat robot "Eliza" was a well-known early attempt at creating programs that could at least temporarily fool a real human being into thinking they were talking to another person. It is a kind of artificial intelligence.
- Micromegas IA / AI programmes/langages ALICE - Open source natural language artificial intelligence chat robot
-
BotSpot
-
- + -
2 Problems
- 2.1 Deduction, reasoning, problem solving
- 2.2 Knowledge representation
- 2.3 Planning
- 2.4 Learning
- 2.5 Natural language processing
- 2.6 Motion and manipulation
- 2.7 Perception
- 2.8 Social intelligence
- 2.9 Creativity
- 2.10 General intelligence
- + -
3 Approaches
- 3.1 Cybernetics and brain simulation
- 3.2 Symbolic
- 3.3 Sub-symbolic
- 3.4 Statistical
- 3.5 Integrating the approaches
- + -
4 Tools
- 4.1 Search and optimization
- 4.2 Logic
- 4.3 Probabilistic methods for uncertain reasoning
- 4.4 Classifiers and statistical learning methods
- 4.5 Neural networks
- 4.6 Control theory
- 4.7 Languages
- 5 Evaluating progress
- + -
6 Applications
- 6.1 Competitions and prizes
- 6.2 Platforms
- 7 Philosophy
- 8 Prediction
- 9 See also
- + -
10 References
- 10.1 AI textbooks
- 10.2 History of AI
- 10.3 Other sources
- 11 Further reading
- 12 External links
- + -
1 History
- + - i
- ~ Sgp
- ~
- ~ Trajectory
- ~ Tasking
- ~ Crystal
- i
- ~ Chat with A.L.I.C.E.
- ~ Chat with GOD
- ~ What is AIML?
- ~ Bot Industry Survey
- ~ AIML Overview
- ~ Foundation Bot Directory
- + -
i
- ~ Effect size
- + -
Form may also refer to:
- Form, a shallow depression or flattened nest of grass used by a hare
- Form (document), a document (printed or electronic) with spaces in which to write or enter data
- Form (education), a class, set or group of students
- Form (exercise), a proper way of performing an exercise
- Form (horse racing), a record of a racehorse's performance, or similarly for an athlete
- Form, a criminal record
- Form, a font designed by Aldo Novarese (1966)
- Form (religion), an academic term for prescriptions or norms on religious practice
- Musical form, a generic type of composition or the structure of a particular piece
- FORM, an American architecture magazine
- + -
Biology:
- Form (botany), a formal taxon at a rank lower than species
- Form (zoology), informal taxa used sometimes in zoology
- + -
Computing:
- Form (web), a document form used on a web page to, typically, submit user data to a server
- Form (programming), a component-based representation of a GUI window
- FORM (symbolic manipulation system), a program for symbolic computations
- Form (computer virus), the most common computer virus of the 1990s
- Oracle Forms, a Rapid Application Development environment for developing database applications
- Windows Forms
- XForms, an XML format for the specification of user interfaces, specifically web forms
- Trapcode Form, a motion graphic editing plug-in from Red Giant Software
- + -
Martial arts:
- Kata (型 or 形), the detailed pattern of defence-and-attack
- Taeguk (Taekwondo) (형), the "forms" used to create a foundation for the teaching of Taekwondo
- Taolu (套路), forms used in Chinese martial arts and sport wushu
- + -
Mathematics:
Algebraic form (homogeneous polynomial), which generalises quadratic forms to degrees 3 and more, also known as quantics or simply forms
Bilinear form, on a vector space V over a field F is a mapping V × V → F that is linear in both arguments
Differential form, a concept from differential topology that combines multi linear forms and smooth functions
Indeterminate form, an algebraic expression that cannot be used to evaluate a limit
Modular form, a (complex) analytic function on the upper half plane satisfying a certain kind of functional equation and growth condition
Multilinear form, which generalises bilinear forms to mappings VN → F
Quadratic form, a homogeneous polynomial of degree two in a number of variables
- + -
Philosophy:
Substantial form
Theory of Forms
Value-form, an approach to understanding the origins of commodity trade and the formation of markets.
- + -
See also
- Formwork, a mould used for concrete construction
- Isoform, several different forms of the same protein
- Sixth form, an English term for the final two years of secondary school
- The Forms (band), an American indie rock band
- Formation (disambiguation)
- Formula (disambiguation)
- Conformity (disambiguation)
- Deformation (disambiguation)
- Inform (disambiguation)
- Reform (disambiguation)
- All pages beginning with "Form"
- All pages with titles containing "Form"
- + -
Form may also refer to:
- Form refers to the shape, visual appearance, or configuration of an object.
- ~ shape
- ~ visual appearance
- ~ configuration
- ~ hare
- ~ Form (document)
- ~ Form (education)
- ~ Form (exercise)
- ~ Form (horse racing)
- ~ criminal record
- ~ Aldo Novarese
- ~ Form (religion)
- ~ Musical form
- ~ FORM
- ~ Form (botany)
- ~ Form (zoology)
- ~ Form (web)
- ~ Form (programming)
- ~ FORM (symbolic manipulation system)
- ~ Form (computer virus)
- ~ Oracle Forms
- ~ Windows Forms
- ~ XForms
- ~ Red Giant Software
- ~ Kata
- ~ Taeguk (Taekwondo)
- ~ Taolu
- ~ homogeneous polynomial
- ~ Bilinear form
- ~ Differential form
- ~ Indeterminate form
- ~ Modular form
- ~ Multilinear form
- ~ Quadratic form
- ~ Substantial form
- ~ Theory of Forms
- ~ Value-form
- ~ edit
- ~ Formwork
- ~ Isoform
- ~ Sixth form
- ~ The Forms (band)
- ~ Formation (disambiguation)
- ~ Formula (disambiguation)
- ~ Conformity (disambiguation)
- ~ Deformation (disambiguation)
- ~ Inform (disambiguation)
- ~ Reform (disambiguation)
- ~ All pages beginning with "Form"
- ~ All pages with titles containing "Form"
- ~ Effect size
- + -
i
- ~ result
- ~ List of effects
- ~ causality
- ~ Drug effect
- ~ Therapeutic effect
- ~ Adverse effect
- ~ dose-response curve
- ~ Special effect
- ~ Sound effect
- ~ Effects unit
- ~ Effects pedal
- ~ Visual effects
- ~ personal property
- ~ All pages beginning with "Effect"
- ~ All pages with titles containing "Effect"
- ~ Affect (disambiguation)
- ~ Effectiveness (disambiguation)
- ~ Efficacy
- ~ Pragmatism
- ~ Corrective strategem
- ~ Artificial Intelligence
- ~
NELL: Never-Ending Language Learning
~ computervisiononline.com > Blog > Never-ending-image-learner
Brain-inspired
- ~ https://code.google.com/p/ahuman/
- ~ en.wikipedia.org > Wiki > Blue Brain Project
- ~ andcorporation.com
- ~ numenta.org > Nupic
- ~ vicarious.com
- ~ tinmansystems.com
- ~ aileenn.com
-
Cognitive architectures
- ~
Automated Option Generation:
-
The focus of Deep Green is on tools to help the commander (and staff) generate options quickly. Leaders from the field generally do not want machine-generated courses of action. Nevertheless, under Deep Green, we intend to sponsor a small set of modest efforts to generate options automatically. The long-term vision of Deep Green is for options to be generated by both the commander and the computer. This highlights the need for Sketch to Plan to induce the commander's intent from the free-hand sketches. Any options generated by the computer should feasibly meet the commander's intent.
+ -
-
APP-6ASymbol Name Strength Constituent units Commander or leader XXXXXX region, theater 1,000,000+ 4+ army groups general, army general, five star general or field marshal XXXXX army group, front 250,000+ 2+ armies general, army general, five star general or field marshal XXXX army 60,000–100,000+ 2–4 corps general, army general, four star general or colonel general XXX corps 30,000–80,000 2+ divisions lieutenant general, corps general or three star general XX division 10,000–20,000 2–4 brigades or regiments major general, divisional general or two star general X brigade 2000–5000 2+ regiments, 3–6 battalions or Commonwealth regiments brigadier general, brigade general, or one star general(sometimes colonel) III regiment or group 2000–3000 2+ battalions or U.S. Cavalry squadrons colonel II infantry battalion, U.S. Cavalry squadron, or Commonwealth armoured regiment 300–1000 2–6 companies, batteries, U.S. Cavalry troops, or Commonwealth squadrons lieutenant colonel I infantry company, artillery battery, U.S. Cavalrytroop, or Commonwealth armour or combat engineering squadron 70–250 2–8 platoons or Commonwealth troops chief warrant officer, captain ormajor ••• platoon or Commonwealth troop 25–60 2+ squads, sections, or vehicles warrant officer, first or secondlieutenant •• section or patrol 8–12 2+ fireteams corporal to sergeant • squad or crew 8–16 2+ fireteams or 1+ cell corporal to staff sergeant Ø fireteam 4–5 n/a lance corporal to sergeant Ø fire and maneuver team 2 n/a any/private first class
+ -
- + -
+ -XXXXXX
+ -XXXXX
+ -XXXX
+ -XXX
+ -XX X + -
- + -
- + -
- + -
- + -
- + -
Ø -
fireteam 4–5 n/a lance corporal to sergeant
Ø -
fire and maneuver team 2 n/a any/private first class
-
- + -
+ -
- + -
III -
regiment or group
+ -II I -
infantry company, artillery battery, U.S. Cavalrytroop, or Commonwealth armour or combat engineering squadron
+ -
- + -
- + -
- + -
- + -
- + -
Ø -
fireteam 4–5 n/a lance corporal to sergeant
Ø -
fire and maneuver team 2 n/a any/private first class
-
- + -
-
+ -
- + -
+ -•••
+ -•• • -
squad or crew
+ -
- + -
- + -
- + -
- + -
- + -
Ø -
fireteam 4–5 n/a lance corporal to sergeant
Ø -
fire and maneuver team 2 n/a any/private first class
-
- + -
-
+ -
- + -
Ø -
fireteam 4–5 n/a lance corporal to sergeant
Ø -
fire and maneuver team 2 n/a any/private first class
+ -
- + -
- + -
- + -
- + -
- + -
Ø -
fireteam 4–5 n/a lance corporal to sergeant
Ø -
fire and maneuver team 2 n/a any/private first class
-
- + -
-
- + -
- + -
- + -
- + -
- + -
Ø -
fireteam 4–5 n/a lance corporal to sergeant
Ø -
fire and maneuver team 2 n/a any/private first class
-
- + -
-
- Collective action, the provision of public goods through collaboration
- Direct action, an instance of political activism
- Group action in mathematics
- Lawsuit, sometimes called a civil action and actio
- Military action (combat), a scale of combat within the hierarchy of combat
- Social actions, which take into account actions and reactions of other individuals
- Strike action, a deliberate absence from work
Sketch to Decide:
-
When the commander is asked for a decision, Sketch to Decide will allow him/her to explore the future space to gain an appreciation for the ramifications of a choice. Sketch to Decide is designed to allow the user to "see the future," but this capability must be developed with care to prevent confusing the decision space. The abstract nature of the state and the uncertainty of predictions, locations of units, etc. must be portrayed intuitively. At any "frame" in the Sketch to Decide graph, the user can perform Sketch to Plan actions, allowing the commander to conduct "what-if" drills wherever he wants in the future space. By presenting decisions early and allowing the commander to explore the future space, Sketch to Decide supports adaptive execution, allowing the commander to make decisions when they are needed, rather than committing too early.
- + -
- + -
+ -XXXXXX
+ -XXXXX
+ -XXXX
+ -XXX
+ -XX X
- + -
- + -
- + -
- + -
- + -
Ø -
fireteam 4–5 n/a lance corporal to sergeant
Ø -
fire and maneuver team 2 n/a any/private first class
-
- + -
- + -
SimPath:
-
SimPath is the simulation component of Deep Green. It is used to generate the possible futures that result from a set of plans (one plan for each side/force in the operation). Besides being very fast, SimPath is designed to generate a broad set of possible futures. These futures should be feasible, even if not expected by human users. Over time, SimPath should learn to be a better predictor of possible futures, based on presented options. SimPath identifies branch points, predicts the range of possible outcomes, predicts the likelihood of each outcome, and then continues to simulate along each path/trajectory. This will require an innovative hybrid of qualitative and quantitative technologies.
~ https://zephyr46.tripod.com/classes/trajectory.html
Crystal Ball:
-
During pre-operations planning, Crystal Ball receives options from Sketch to Plan for all sides and forces. Crystal ball assembles the permutations of plans and sends them to SimPath to generate the possible futures that result from each permutation. SimPath returns sub-graphs of possible futures and branch points to Crystal Ball with annotations as to SimPath's a priori estimate of the likelihood of these options. Another function of Crystal Ball is to merge these sub-graphs so the futures that are qualitatively the same (regardless of which permutation of options generated them) are combined. Once the operation is underway, Crystal Ball will get information about the ongoing operation from the battle command systems. Crystal Ball uses this information about the current operation to update the likelihood estimates of the many possible futures. Having done that, Crystal Ball can compare the likelihood, utility, and flexibility and estimate which futures are likely to occur that have little value or flexibility. Crystal Ball will use this estimate to nominate to the commander futures at which he/she should focus some planning effort to build additional options/branches. If the commander reaches a future for which no options have been developed, he/she has been surprised and the enemy is now operating inside his/her decision cycle. Crystal Ball will also use this information and additional heuristics to nominate futures for pruning from the graph and to identify decision points to send to Sketch to Decide. Pruning, however, will not be based purely on likelihood, but also on attributes such as risk to the operation.
- ~
http://www.darpa.mil/ipto/programs/dg/dg.asp
~
http://www.defenseindustrydaily.com/files/PUB_BAA_DARPA_07-56_Deep_Green.pdf
+ - Spectrum
- ~ Blue Pilot
- ~ Red Pilot
- ~ Orange Pilot
- ~ White Pilot
- + -
Yellow Pilot
- HSCB
-
CAPABILITIES
-
HSCB programs are organized into four capabilities, each set feeding into the next and forming a cycle.
+ --
Understand
Understand sociocultural parameters of operational environment.
-
Capabilities to support thorough perception and comprehension, grounded in social and behavioral science, of the sociocultural features and dynamics in an operational environment.
The cycle begins with the need to frame the sociocultural structure and dynamics of behavior in a given operational context. To understand at this level means bringing sociocultural theory and concepts to bear to identify the sociocultural features of the terrain that are important to monitor. Understanding is not a single event, and users may constantly need to adapt the initially-applied theories, concepts, and consequent features based on the results of detecting, forecasting, and mitigation. This then initiates a new cycle. This step spans all levels - tactical, operational, and strategic. It requires applied social and behavioral science theory, access to baseline sociocultural data for any given region, descriptive models, and linguistic and sociocultural training.
-
Detect
Detect valid sociocultural behavior signals from noise.
-
Capabilities to discover, distinguish, and locate operationally relevant sociocultural signatures through the collection, processing, and analysis of sociocultural behavior data.
Once the defining features of the sociocultural setting are understood, the next steps are to develop a persistent capability to detect sociocultural behavior signals of interest amidst complexity and noise, and to harvest data for analysis. This entails capabilities for ISR in the area of sociocultural behavior (referred to here as a "social radar"), with particular focus on the challenges associated with open source data collection. It also requires robust systems for storing and managing that data, and tools enabling timely, dynamic analysis.
-
Forecast
Forecast behaviors in response to possible COAs.
-
Capabilities for tracking and forecasting change in entities and phenomena of interest along multiple dimensions (time, space, social networks, types of behavior, etc.) through persistent sensing and modeling of the environment.
Armed with historical and real-time data, users can take the next step: to forecast alternative plausible futures by extrapolating from the collected data. The goals are to identify the various paths that behaviors of interest could take, and to estimate the consequences of each for populations of interest. Among the most important needs in this step are large amounts of data, multidisciplinary theory, and hybrid modeling.
-
Mitigate
Mitigate behaviors and measure effects.
-
Capabilities to develop, prioritize, execute, and measure COAs grounded in the social and behavioral sciences.
The final step in the cycle is to develop and measure the effects of alternative COAs for achieving desired changes. This step builds on all the foregoing ones, and should assist in updating U.S. forces' understanding of the sociocultural behavior terrain, thus continuing the cycle. This step requires education in the use of models for robust decision making, strategic-level theory, integrated systems, decision space visualization, and agile data collection.
OTHER SOCIOCULTURAL PROGRAMS
Minerva
Strategic Multi-Layer Assessment (SMA)
National Science Foundation's Directorate for Social, Behavioral and Economic Sciences
Air Force Office of Scientific Research Collective Behavior and Socio-Cultural Modeling
Air Force Research Laboratory Human Effectiveness Directorate (RH)
- Anticipate and Influence Behavior Division
- National Operational Environment Model
U.S. Army Corps of Engineers (USACE)
- Army Geospatial Center (AGC)
- Measuring Progress in Conflict Environments (MPICE)
U.S. Army Research Institute for the Behavioral and Social Sciences (ARI) Learning and Operating in Culturally Unfamiliar Settings (LOCUS)
U.S. Army Research Laboratory (ARL)
- Human Research and Engineering Directorate
- Network Science Collaborative Technology Alliance
U.S. Army Training and Doctrine Command (TRADOC)
- Cultural Knowledge Consortium (CKC)
- Human Terrain System
Office of Naval Research (ONR) Affordable Human Behavior Modeling (AHBM)
-
Understand
Test areas
- + - Syria
- + - Somalia
- + - Nigeria
- + - Bangladesh
Process
-
-
- HSCB
- ~ Green Pilot
-
- Indigo
- Archive
- ~ https://web.archive.org/web/20130219055023/https://zephyr46.tripod.com/fynderpresponse/
- ~ https://web.archive.org/web/20130104051236/https://zephyr46.tripod.com/salt/id11.html
- ~ https://web.archive.org/web/20130104051213/https://zephyr46.tripod.com/salt/
- Earthbank
- ~ https://web.archive.org/web/20130219055004/https://zephyr46.tripod.com/fynderpresponse/id12.html
- + -
~ Orders of magnitude
~ Orders of magnitude (length)
~ Visualisation + - ~
- ~ 20th century
- ~ Periodization
- ~ Planck_time
- ~ Time (Orders of magnitude)
- yoctosecond zeptosecond
- ~ Attosecond
- ~ Femtosecond
- ~ Picosecond
- ~ Nanosecond
- ~ Microsecond
- ~ Millisecond
- ~ Second
- + -
~ Minute
- ~ Utopia
- ~ List of freedom indices
- ~ Homeostasis
-
DirectionologyMilky Way and Andromeda galaxy are approaching each other with a speed of about 130 km/s, however the collision of these two galaxies will not occur for about 5 billion years (AstroFile). Another result I found was that our galaxy and neighbors are moving at 600 km/s in the direction of the constellation Hydra (Scientific American). Finally, I found that the Milky Way moves through space within the cluster of galaxies it is a member of, and this cluster in turn moves through space towards yet another larger cluster of galaxies off in the direction of the constellation Virgo. This speed is approximately 300 km/s (Ask the Space Scientist). Therefore, the speed of the Milky Way galaxy is not a single number, its value is relative to the speed of other objects.Survey effects of scale motions with pioneer and voyager type robots, effects of gravity over distence. Probes targeted towards and opposition, to measure velocities and resistences.Andromeda_GalaxyVirgo_supercluster
Since the late 1980s it has been apparent that not only the Local Group, but all matter out to a distance of at least 50 Mpc is experiencing a bulk flow on the order of 600 km/sec in the direction of the Norma cluster (Abell 3627).[10] Lynden-Bell et al. (1988) dubbed the cause of this "The Great Attractor." While astronomers are confident of the velocity of the LS, which has been measured against the Cosmic Microwave Background (CMB), the nature of what is causing it remains poorly understood.
-
- ~ Intersectionality
- ~ Conflict
- ~ Dystopia
- ~ 21st century
- ~ Kilosecond
- ~ Hour
- ~ Megasecond
- 11.6 days
- ~ Gigasecond
- 31.558 years
- ~ 22nd century
- ~ Terasecond and longer
-
Teraseconds
-
Petaseconds
-
Exaseconds
-
Zettaseconds
-
Yottaseconds
-
- megametre
- terametre
- petametre
- Archive
- Sense
- Calabration
- Indigo
- ~ Effect size
- ~ Trajectory
- ~ Homeostasis
- ~ Intersectionality
- ~ Conflict
- ~ Dystopia
- ~ 2016
- ~ 2017
- ~ 2018
- ~ 2019
- ~ 2020s
- ~ 2030s
- ~ 2040s
- ~ Minute
- ~ Kilosecond
- ~ Hour
- ~ Megasecond
- 11.6 days
- ~ Gigasecond
- 31.558 years
- ~ 22nd century
- + -
~ Terasecond and longer
-
Teraseconds
-
Petaseconds
-
Exaseconds
-
Zettaseconds
-
Yottaseconds
-
- ~ 2016
-
- January
-
+ -
-
APP-6ASymbol Name Strength Constituent units Commander or leader XXXXXX region, theater 1,000,000+ 4+ army groups general, army general, five star general or field marshal XXXXX army group, front 250,000+ 2+ armies general, army general, five star general or field marshal XXXX army 60,000–100,000+ 2–4 corps general, army general, four star general or colonel general XXX corps 30,000–80,000 2+ divisions lieutenant general, corps general or three star general XX division 10,000–20,000 2–4 brigades or regiments major general, divisional general or two star general X brigade 2000–5000 2+ regiments, 3–6 battalions or Commonwealth regiments brigadier general, brigade general, or one star general(sometimes colonel) III regiment or group 2000–3000 2+ battalions or U.S. Cavalry squadrons colonel II infantry battalion, U.S. Cavalry squadron, or Commonwealth armoured regiment 300–1000 2–6 companies, batteries, U.S. Cavalry troops, or Commonwealth squadrons lieutenant colonel I infantry company, artillery battery, U.S. Cavalrytroop, or Commonwealth armour or combat engineering squadron 70–250 2–8 platoons or Commonwealth troops chief warrant officer, captain ormajor ••• platoon or Commonwealth troop 25–60 2+ squads, sections, or vehicles warrant officer, first or secondlieutenant •• section or patrol 8–12 2+ fireteams corporal to sergeant • squad or crew 8–16 2+ fireteams or 1+ cell corporal to staff sergeant Ø fireteam 4–5 n/a lance corporal to sergeant Ø fire and maneuver team 2 n/a any/private first class
+ -
- + -
+ -XXXXXX
+ -XXXXX
+ -XXXX
+ -XXX
+ -XX X + -
- + -
- + -
- + -
- + -
- + -
Ø -
fireteam 4–5 n/a lance corporal to sergeant
Ø -
fire and maneuver team 2 n/a any/private first class
-
- + -
+ -
- + -
III -
regiment or group
+ -II I -
infantry company, artillery battery, U.S. Cavalrytroop, or Commonwealth armour or combat engineering squadron
+ -
- + -
- + -
- + -
- + -
- + -
Ø -
fireteam 4–5 n/a lance corporal to sergeant
Ø -
fire and maneuver team 2 n/a any/private first class
-
- + -
-
+ -
- + -
+ -•••
+ -•• • -
squad or crew
+ -
- + -
- + -
- + -
- + -
- + -
Ø -
fireteam 4–5 n/a lance corporal to sergeant
Ø -
fire and maneuver team 2 n/a any/private first class
-
- + -
-
+ -
- + -
Ø -
fireteam 4–5 n/a lance corporal to sergeant
Ø -
fire and maneuver team 2 n/a any/private first class
+ -
- + -
- + -
- + -
- + -
- + -
Ø -
fireteam 4–5 n/a lance corporal to sergeant
Ø -
fire and maneuver team 2 n/a any/private first class
-
- + -
-
- + -
- + -
- + -
- + -
- + -
Ø -
fireteam 4–5 n/a lance corporal to sergeant
Ø -
fire and maneuver team 2 n/a any/private first class
-
- + -
-
-
- Febuary
- March
- April
- May
- June
- July
- August
- September
- October
- November
- December
- January
-
- ~ 2017
- + -
- January
- Febuary
- March
- April
- May
- June
- July
- August
- September
- October
- November
- December
- + -
- ~ 2018
- + -
- January
- Febuary
- March
- April
- May
- June
- July
- August
- September
- October
- November
- December
- + -
- ~ 2019
- + -
- January
- Febuary
- March
- April
- May
- June
- July
- August
- September
- October
- November
- December
- + -
- ~ 2020s
- ~ 2030s
- ~ 2040s
- ~ 22nd century
- ~
- + -
HSCB
Commander's Associate:
-
This component provides the commander the ability to generate quickly qualitative, coarse-grained COA sketches that the computer can interpret. Sketch to Plan will be multi-modal (both sketching and speech) and interactive. The computer will watch the sketch being drawn and listen for key words that indicate sequence, time, intent, etc. as the commander is creating the sketch. Sketch to Plan will induce both a plan and the commander's intent from the sketch and speech. The Sketch to Plan component must be imbued with enough domain knowledge that it knows what it doesn't know and can ask the user a small set of clarifying questions until it understands the sketch and can use it to initialize a combat model. Finally, the dialog generator helps Sketch to Plan understand the commander's option by formulating clarifying questions when necessary.
~ http://zephyr9673.tripod.com/class/I%20pilot%20two.html+ - i
- + - ~ 1 History
- + -
Strong AI
+ - i
- ~ artificial intelligence
- ~ intelligence
- ~ [1]
- ~ artificial intelligence
- ~ science fiction
- ~ futurists
- ~ [2]
- ~ [3]
- ~ Science fiction
- ~ consciousness
- ~ sentience
- ~ sapience
- ~ self-awareness
- ~ applied AI
- ~ [4]
- ~ [1]
- ~ [5]
- ~ problem solving
- ~ reasoning
Strong AI is artificial intelligence that matches or exceeds human intelligence — the intelligence of a machine that can successfully perform any intellectual task that a human being can.[1] It is a primary goal of artificial intelligence research and an important topic for science fiction writers and futurists. Strong AI is also referred to as "artificial general intelligence"[2] or as the ability to perform "general intelligent action".[3] Science fiction associates strong AI with such human traits as consciousness, sentience, sapience and self-awareness.
Some references emphasize a distinction between strong AI and "applied AI"[4] (also called "narrow AI"[1] or "weak AI"[5]): the use of software to study or accomplish specific problem solving or reasoning tasks that do not encompass (or in some cases are completely outside of) the full range of human cognitive abilities.
- ~ 7 Philosophy
- + - ~ 8 Prediction
- + - ~ 4 Tools
- + -
Contents
- + -
1 History
-
Web Directories, Dictionaries and Encyclopedias
-
BotSpot
What's a Bot?
In short: A bot is a software tool for digging through data. You give a bot directions and it bring back answers. The word is short for robot of course, which is derived from the Czech word robota meaning work.
The idea of robots as humanoid machines was first introduced in Karel Capek's 1921 play "R.U.R.," where the playwright conceived Rossum's Universal Robots. Sci-fi writer Isaac Asimov made them famous, beginning with his story I, Robot (1950) and continuing through a string of books known as the Robot Series (see the Isaac Asimov FAQ - for more details including "The Three Laws of Robotics"). - Easily Amused dot com Welcome o' yee of short attention span. Presented here is a collected list of web sites which I found amusing. Although my opinion will vary greatly from yours I hope that you find the majority of these sites at least worth the mouse click to access them.
- Wikipedia A.L.I.C.E. (Artificial Linguistic Internet Computer Entity) is an award-winning natural language processing chatterbot . a program that engages in a conversation with a human by applying some heuristical pattern matching rules to the human's input. It was inspired by Joseph Weizenbaum's classical ELIZA program but takes a quite different approach. It is one of the strongest programs of its type and has won the Loebner Prize three times (in 2000, 2001 and 2004).
- Agentland.com Alice (Artificial Linguistic Internet Computer Entity) is a natural language interface to a telerobot eye. Alice tries ironically to be a computer, so her replies may make some sense but in reality Alice is nothing more than a gigantic pattern-matching case-statement. Remarkably however this elaborate hoax has produced some of the most convincing natural conversations between computer andx humans yet observed.
- Open Directory Chatterbots: ALICE Computers: Artificial Intelligence: Natural Language: Chatterbots: ALICE
- AAAI AI Ethics Any sci-fi buff knows that when computers become self-aware, they ultimately destroy their creators. From 2001: A Space Odyssey to Terminator, the message is clear: The only good self-aware machine is an unplugged one. We may soon find out whether that's true. ... But what about HAL 9000 and the other fictional computers that have run amok?
- American Association for Artificial Intelligence A.I. topics -- Natural LanguageThe value to our society of being able to communicate with computers in everyday "natural" language cannot be overstated. Imagine asking your computer "Does this candidate have a good record on the environment?" or "When is the next televised National League baseball game?" Or being able to tell your PC "Please format my homework the way my English professor likes it".
- American Association for Artificial Intelligence A.I. topics -- The Turing TestAlan Turing proposed an operational test of intelligence as a replacement for the philosophical question, "Can machines think?" Variations of this test have been used to assess performance levels of many AI programs. A restricted adaptation of the Turing Test popularized by the Loebner Competition has been fun, although currently many AI scientists criticize the restricted version of the test because it does not provide insights into the mechanisms of thought.
- www.cs.um.edu.mt/~mros/nlp/ NLP Resource Page
- members.aol.com/lshauser/aiothers.html AI & Other Minds by Larry Hauser.
- www.faqs.org/faqs/ai-faq/general/part6/ Artificial Intelligence FAQ: Open Source AI Software "Chatbots: AI: There is a much maligned chatbot at the Warner Brothers page on the AI movie."
- Sitereview.org A.L.I.C.E is an "Artificial Linguistic Internet Computer Entity" capable of intelligent conversation. She will amaze you with her ability to come up with a relevant response to just about anything! If I didn't know better, I'd think she was human.
- You can become a Botmaster A chat robot is a program that attempts to simulate the conversation or "chat" of a human being. The Chat robot "Eliza" was a well-known early attempt at creating programs that could at least temporarily fool a real human being into thinking they were talking to another person. It is a kind of artificial intelligence.
- Micromegas IA / AI programmes/langages ALICE - Open source natural language artificial intelligence chat robot
-
BotSpot
-
- + -
2 Problems
- 2.1 Deduction, reasoning, problem solving
- 2.2 Knowledge representation
- 2.3 Planning
- 2.4 Learning
- 2.5 Natural language processing
- 2.6 Motion and manipulation
- 2.7 Perception
- 2.8 Social intelligence
- 2.9 Creativity
- 2.10 General intelligence
- + -
3 Approaches
- 3.1 Cybernetics and brain simulation
- 3.2 Symbolic
- 3.3 Sub-symbolic
- 3.4 Statistical
- 3.5 Integrating the approaches
- + -
4 Tools
- 4.1 Search and optimization
- 4.2 Logic
- 4.3 Probabilistic methods for uncertain reasoning
- 4.4 Classifiers and statistical learning methods
- 4.5 Neural networks
- 4.6 Control theory
- 4.7 Languages
- 5 Evaluating progress
- + -
6 Applications
- 6.1 Competitions and prizes
- 6.2 Platforms
- 7 Philosophy
- 8 Prediction
- 9 See also
- + -
10 References
- 10.1 AI textbooks
- 10.2 History of AI
- 10.3 Other sources
- 11 Further reading
- 12 External links
- + -
1 History
- + - i
- ~ Sgp
- ~
- ~ Trajectory
- ~ Tasking
- ~ Crystal
- i
- ~ Chat with A.L.I.C.E.
- ~ Chat with GOD
- ~ What is AIML?
- ~ Bot Industry Survey
- ~ AIML Overview
- ~ Foundation Bot Directory
- + -
i
- ~ Effect size
- + -
Form may also refer to:
- Form, a shallow depression or flattened nest of grass used by a hare
- Form (document), a document (printed or electronic) with spaces in which to write or enter data
- Form (education), a class, set or group of students
- Form (exercise), a proper way of performing an exercise
- Form (horse racing), a record of a racehorse's performance, or similarly for an athlete
- Form, a criminal record
- Form, a font designed by Aldo Novarese (1966)
- Form (religion), an academic term for prescriptions or norms on religious practice
- Musical form, a generic type of composition or the structure of a particular piece
- FORM, an American architecture magazine
- + -
Biology:
- Form (botany), a formal taxon at a rank lower than species
- Form (zoology), informal taxa used sometimes in zoology
- + -
Computing:
- Form (web), a document form used on a web page to, typically, submit user data to a server
- Form (programming), a component-based representation of a GUI window
- FORM (symbolic manipulation system), a program for symbolic computations
- Form (computer virus), the most common computer virus of the 1990s
- Oracle Forms, a Rapid Application Development environment for developing database applications
- Windows Forms
- XForms, an XML format for the specification of user interfaces, specifically web forms
- Trapcode Form, a motion graphic editing plug-in from Red Giant Software
- + -
Martial arts:
- Kata (型 or 形), the detailed pattern of defence-and-attack
- Taeguk (Taekwondo) (형), the "forms" used to create a foundation for the teaching of Taekwondo
- Taolu (套路), forms used in Chinese martial arts and sport wushu
- + -
Mathematics:
Algebraic form (homogeneous polynomial), which generalises quadratic forms to degrees 3 and more, also known as quantics or simply forms
Bilinear form, on a vector space V over a field F is a mapping V × V → F that is linear in both arguments
Differential form, a concept from differential topology that combines multi linear forms and smooth functions
Indeterminate form, an algebraic expression that cannot be used to evaluate a limit
Modular form, a (complex) analytic function on the upper half plane satisfying a certain kind of functional equation and growth condition
Multilinear form, which generalises bilinear forms to mappings VN → F
Quadratic form, a homogeneous polynomial of degree two in a number of variables
- + -
Philosophy:
Substantial form
Theory of Forms
Value-form, an approach to understanding the origins of commodity trade and the formation of markets.
- + -
See also
- Formwork, a mould used for concrete construction
- Isoform, several different forms of the same protein
- Sixth form, an English term for the final two years of secondary school
- The Forms (band), an American indie rock band
- Formation (disambiguation)
- Formula (disambiguation)
- Conformity (disambiguation)
- Deformation (disambiguation)
- Inform (disambiguation)
- Reform (disambiguation)
- All pages beginning with "Form"
- All pages with titles containing "Form"
- + -
Form may also refer to:
- Form refers to the shape, visual appearance, or configuration of an object.
- ~ shape
- ~ visual appearance
- ~ configuration
- ~ hare
- ~ Form (document)
- ~ Form (education)
- ~ Form (exercise)
- ~ Form (horse racing)
- ~ criminal record
- ~ Aldo Novarese
- ~ Form (religion)
- ~ Musical form
- ~ FORM
- ~ Form (botany)
- ~ Form (zoology)
- ~ Form (web)
- ~ Form (programming)
- ~ FORM (symbolic manipulation system)
- ~ Form (computer virus)
- ~ Oracle Forms
- ~ Windows Forms
- ~ XForms
- ~ Red Giant Software
- ~ Kata
- ~ Taeguk (Taekwondo)
- ~ Taolu
- ~ homogeneous polynomial
- ~ Bilinear form
- ~ Differential form
- ~ Indeterminate form
- ~ Modular form
- ~ Multilinear form
- ~ Quadratic form
- ~ Substantial form
- ~ Theory of Forms
- ~ Value-form
- ~ edit
- ~ Formwork
- ~ Isoform
- ~ Sixth form
- ~ The Forms (band)
- ~ Formation (disambiguation)
- ~ Formula (disambiguation)
- ~ Conformity (disambiguation)
- ~ Deformation (disambiguation)
- ~ Inform (disambiguation)
- ~ Reform (disambiguation)
- ~ All pages beginning with "Form"
- ~ All pages with titles containing "Form"
- ~ Effect size
- + -
i
- ~ result
- ~ List of effects
- ~ causality
- ~ Drug effect
- ~ Therapeutic effect
- ~ Adverse effect
- ~ dose-response curve
- ~ Special effect
- ~ Sound effect
- ~ Effects unit
- ~ Effects pedal
- ~ Visual effects
- ~ personal property
- ~ All pages beginning with "Effect"
- ~ All pages with titles containing "Effect"
- ~ Affect (disambiguation)
- ~ Effectiveness (disambiguation)
- ~ Efficacy
- ~ Pragmatism
- ~ Corrective strategem
- ~ Artificial Intelligence
- ~
NELL: Never-Ending Language Learning
~ computervisiononline.com > Blog > Never-ending-image-learner
Brain-inspired
- ~ https://code.google.com/p/ahuman/
- ~ en.wikipedia.org > Wiki > Blue Brain Project
- ~ andcorporation.com
- ~ numenta.org > Nupic
- ~ vicarious.com
- ~ tinmansystems.com
- ~ aileenn.com
-
Cognitive architectures
- ~
Automated Option Generation:
-
The focus of Deep Green is on tools to help the commander (and staff) generate options quickly. Leaders from the field generally do not want machine-generated courses of action. Nevertheless, under Deep Green, we intend to sponsor a small set of modest efforts to generate options automatically. The long-term vision of Deep Green is for options to be generated by both the commander and the computer. This highlights the need for Sketch to Plan to induce the commander's intent from the free-hand sketches. Any options generated by the computer should feasibly meet the commander's intent.
+ -
-
APP-6ASymbol Name Strength Constituent units Commander or leader XXXXXX region, theater 1,000,000+ 4+ army groups general, army general, five star general or field marshal XXXXX army group, front 250,000+ 2+ armies general, army general, five star general or field marshal XXXX army 60,000–100,000+ 2–4 corps general, army general, four star general or colonel general XXX corps 30,000–80,000 2+ divisions lieutenant general, corps general or three star general XX division 10,000–20,000 2–4 brigades or regiments major general, divisional general or two star general X brigade 2000–5000 2+ regiments, 3–6 battalions or Commonwealth regiments brigadier general, brigade general, or one star general(sometimes colonel) III regiment or group 2000–3000 2+ battalions or U.S. Cavalry squadrons colonel II infantry battalion, U.S. Cavalry squadron, or Commonwealth armoured regiment 300–1000 2–6 companies, batteries, U.S. Cavalry troops, or Commonwealth squadrons lieutenant colonel I infantry company, artillery battery, U.S. Cavalrytroop, or Commonwealth armour or combat engineering squadron 70–250 2–8 platoons or Commonwealth troops chief warrant officer, captain ormajor ••• platoon or Commonwealth troop 25–60 2+ squads, sections, or vehicles warrant officer, first or secondlieutenant •• section or patrol 8–12 2+ fireteams corporal to sergeant • squad or crew 8–16 2+ fireteams or 1+ cell corporal to staff sergeant Ø fireteam 4–5 n/a lance corporal to sergeant Ø fire and maneuver team 2 n/a any/private first class
+ -
- + -
+ -XXXXXX
+ -XXXXX
+ -XXXX
+ -XXX
+ -XX X + -
- + -
- + -
- + -
- + -
- + -
Ø -
fireteam 4–5 n/a lance corporal to sergeant
Ø -
fire and maneuver team 2 n/a any/private first class
-
- + -
+ -
- + -
III -
regiment or group
+ -II I -
infantry company, artillery battery, U.S. Cavalrytroop, or Commonwealth armour or combat engineering squadron
+ -
- + -
- + -
- + -
- + -
- + -
Ø -
fireteam 4–5 n/a lance corporal to sergeant
Ø -
fire and maneuver team 2 n/a any/private first class
-
- + -
-
+ -
- + -
+ -•••
+ -•• • -
squad or crew
+ -
- + -
- + -
- + -
- + -
- + -
Ø -
fireteam 4–5 n/a lance corporal to sergeant
Ø -
fire and maneuver team 2 n/a any/private first class
-
- + -
-
+ -
- + -
Ø -
fireteam 4–5 n/a lance corporal to sergeant
Ø -
fire and maneuver team 2 n/a any/private first class
+ -
- + -
- + -
- + -
- + -
- + -
Ø -
fireteam 4–5 n/a lance corporal to sergeant
Ø -
fire and maneuver team 2 n/a any/private first class
-
- + -
-
- + -
- + -
- + -
- + -
- + -
Ø -
fireteam 4–5 n/a lance corporal to sergeant
Ø -
fire and maneuver team 2 n/a any/private first class
-
- + -
-
- Collective action, the provision of public goods through collaboration
- Direct action, an instance of political activism
- Group action in mathematics
- Lawsuit, sometimes called a civil action and actio
- Military action (combat), a scale of combat within the hierarchy of combat
- Social actions, which take into account actions and reactions of other individuals
- Strike action, a deliberate absence from work
Sketch to Decide:
-
When the commander is asked for a decision, Sketch to Decide will allow him/her to explore the future space to gain an appreciation for the ramifications of a choice. Sketch to Decide is designed to allow the user to "see the future," but this capability must be developed with care to prevent confusing the decision space. The abstract nature of the state and the uncertainty of predictions, locations of units, etc. must be portrayed intuitively. At any "frame" in the Sketch to Decide graph, the user can perform Sketch to Plan actions, allowing the commander to conduct "what-if" drills wherever he wants in the future space. By presenting decisions early and allowing the commander to explore the future space, Sketch to Decide supports adaptive execution, allowing the commander to make decisions when they are needed, rather than committing too early.
- + -
- + -
+ -XXXXXX
+ -XXXXX
+ -XXXX
+ -XXX
+ -XX X
- + -
- + -
- + -
- + -
- + -
Ø -
fireteam 4–5 n/a lance corporal to sergeant
Ø -
fire and maneuver team 2 n/a any/private first class
-
- + -
+ - ~ 21st century
- ~ List of terrorist incidents, 2015
- ~
M
- ~ 20th century
- ~ Periodization
- ~ Planck_time
- ~ Time (Orders of magnitude)
- yoctosecond zeptosecond
- ~ Attosecond
- ~ Femtosecond
- ~ Picosecond
- ~ Nanosecond
- ~ Microsecond
- ~ Millisecond
- ~ Second
- + -
~ Minute
- ~ Utopia
- ~ List of freedom indices
- ~ Homeostasis
-
DirectionologyMilky Way and Andromeda galaxy are approaching each other with a speed of about 130 km/s, however the collision of these two galaxies will not occur for about 5 billion years (AstroFile). Another result I found was that our galaxy and neighbors are moving at 600 km/s in the direction of the constellation Hydra (Scientific American). Finally, I found that the Milky Way moves through space within the cluster of galaxies it is a member of, and this cluster in turn moves through space towards yet another larger cluster of galaxies off in the direction of the constellation Virgo. This speed is approximately 300 km/s (Ask the Space Scientist). Therefore, the speed of the Milky Way galaxy is not a single number, its value is relative to the speed of other objects.Survey effects of scale motions with pioneer and voyager type robots, effects of gravity over distence. Probes targeted towards and opposition, to measure velocities and resistences.Andromeda_GalaxyVirgo_supercluster
Since the late 1980s it has been apparent that not only the Local Group, but all matter out to a distance of at least 50 Mpc is experiencing a bulk flow on the order of 600 km/sec in the direction of the Norma cluster (Abell 3627).[10] Lynden-Bell et al. (1988) dubbed the cause of this "The Great Attractor." While astronomers are confident of the velocity of the LS, which has been measured against the Cosmic Microwave Background (CMB), the nature of what is causing it remains poorly understood.
-
- ~ Intersectionality
- ~ Conflict
- ~ Dystopia
- ~ 21st century
- ~ Minute
- ~ Utopia
- ~ List of freedom indices
-
+ - i
- ~ Effect size
- + -
Form may also refer to:
- Form, a shallow depression or flattened nest of grass used by a hare
- Form (document), a document (printed or electronic) with spaces in which to write or enter data
- Form (education), a class, set or group of students
- Form (exercise), a proper way of performing an exercise
- Form (horse racing), a record of a racehorse's performance, or similarly for an athlete
- Form, a criminal record
- Form, a font designed by Aldo Novarese (1966)
- Form (religion), an academic term for prescriptions or norms on religious practice
- Musical form, a generic type of composition or the structure of a particular piece
- FORM, an American architecture magazine
- + -
Biology:
- Form (botany), a formal taxon at a rank lower than species
- Form (zoology), informal taxa used sometimes in zoology
- + -
Computing:
- Form (web), a document form used on a web page to, typically, submit user data to a server
- Form (programming), a component-based representation of a GUI window
- FORM (symbolic manipulation system), a program for symbolic computations
- Form (computer virus), the most common computer virus of the 1990s
- Oracle Forms, a Rapid Application Development environment for developing database applications
- Windows Forms
- XForms, an XML format for the specification of user interfaces, specifically web forms
- Trapcode Form, a motion graphic editing plug-in from Red Giant Software
- + -
Martial arts:
- Kata (型 or 形), the detailed pattern of defence-and-attack
- Taeguk (Taekwondo) (형), the "forms" used to create a foundation for the teaching of Taekwondo
- Taolu (套路), forms used in Chinese martial arts and sport wushu
- + -
Mathematics:
Algebraic form (homogeneous polynomial), which generalises quadratic forms to degrees 3 and more, also known as quantics or simply forms
Bilinear form, on a vector space V over a field F is a mapping V × V → F that is linear in both arguments
Differential form, a concept from differential topology that combines multi linear forms and smooth functions
Indeterminate form, an algebraic expression that cannot be used to evaluate a limit
Modular form, a (complex) analytic function on the upper half plane satisfying a certain kind of functional equation and growth condition
Multilinear form, which generalises bilinear forms to mappings VN → F
Quadratic form, a homogeneous polynomial of degree two in a number of variables
- + -
Philosophy:
Substantial form
Theory of Forms
Value-form, an approach to understanding the origins of commodity trade and the formation of markets.
- + -
See also
- Formwork, a mould used for concrete construction
- Isoform, several different forms of the same protein
- Sixth form, an English term for the final two years of secondary school
- The Forms (band), an American indie rock band
- Formation (disambiguation)
- Formula (disambiguation)
- Conformity (disambiguation)
- Deformation (disambiguation)
- Inform (disambiguation)
- Reform (disambiguation)
- All pages beginning with "Form"
- All pages with titles containing "Form"
- + -
Form may also refer to:
- Form refers to the shape, visual appearance, or configuration of an object.
- ~ shape
- ~ visual appearance
- ~ configuration
- ~ hare
- ~ Form (document)
- ~ Form (education)
- ~ Form (exercise)
- ~ Form (horse racing)
- ~ criminal record
- ~ Aldo Novarese
- ~ Form (religion)
- ~ Musical form
- ~ FORM
- ~ Form (botany)
- ~ Form (zoology)
- ~ Form (web)
- ~ Form (programming)
- ~ FORM (symbolic manipulation system)
- ~ Form (computer virus)
- ~ Oracle Forms
- ~ Windows Forms
- ~ XForms
- ~ Red Giant Software
- ~ Kata
- ~ Taeguk (Taekwondo)
- ~ Taolu
- ~ homogeneous polynomial
- ~ Bilinear form
- ~ Differential form
- ~ Indeterminate form
- ~ Modular form
- ~ Multilinear form
- ~ Quadratic form
- ~ Substantial form
- ~ Theory of Forms
- ~ Value-form
- ~ edit
- ~ Formwork
- ~ Isoform
- ~ Sixth form
- ~ The Forms (band)
- ~ Formation (disambiguation)
- ~ Formula (disambiguation)
- ~ Conformity (disambiguation)
- ~ Deformation (disambiguation)
- ~ Inform (disambiguation)
- ~ Reform (disambiguation)
- ~ All pages beginning with "Form"
- ~ All pages with titles containing "Form"
+ - i
- ~ result
- ~ List of effects
- ~ causality
- ~ Drug effect
- ~ Therapeutic effect
- ~ Adverse effect
- ~ dose-response curve
- ~ Special effect
- ~ Sound effect
- ~ Effects unit
- ~ Effects pedal
- ~ Visual effects
- ~ personal property
- ~ All pages beginning with "Effect"
- ~ All pages with titles containing "Effect"
- ~ Affect (disambiguation)
- ~ Effectiveness (disambiguation)
- ~ Efficacy
- ~ Pragmatism
Mission:
- + -
Deep Green (DG)
Program Manager: Dr. Todd Hughes (AEO)- ~
http://www.darpa.mil/ipto/programs/dg/dg.asp
~
http://www.defenseindustrydaily.com/files/PUB_BAA_DARPA_07-56_Deep_Green.pdf
The Deep Green concept is an innovative approach to using simulation to support ongoing military operations while they are being conducted. The basic approach is to maintain a state-space graph of possible future states. Software agents use information on the trajectory of the ongoing operation, vice a priori staff estimates as to how the battle might unfold, as well as simulation technologies, to assess the likelihood of reaching some set of possible future states. The likelihood, utility, and flexibility of possible future nodes in the state space graph are computed and evaluated to focus the planning efforts. This notion is called anticipatory planning and involves the generation of options (either manual or semi-automated) ahead of "real time," before the options are needed. In addition, the Deep Green concept provides mechanisms for adaptive execution, which can be described as "late binding," or choosing a branch in the state space graph at the last moment to maintain flexibility. By using information acquired from the ongoing operation, rather than assumptions made during the planning phase, commanders and staffs can make more informed choices and focus on building options for futures that are becoming more likely.
Deep Learning
- ~
http://www.darpa.mil/ipto/programs/deep/deep.asp
+ -
Vision:
-
The Deep Learning program will discover and instantiate in a learning machine (Deep Learning System) a single set of methods that, when applied repeatedly across multiple layers of the machine, yield more useful representations of audio/visual, sensor, and language information, using less labeled data more efficiently than any existing technologies.
Mission:
-
The Deep Learning program aims to revolutionize machine learning by creating a new class of learning machines that overcome the computational limitations of current "shallow" learning machines. This will be done by building machines that can use many layers of processing in a manner that is, at least superficially, similar to that used by biological brains. The Deep Learning program will develop a Core Deep Learner that creates rich encodings of input data by using the same set of algorithms across multiple layers and will demonstrate that the Core Deep Learner can be applied successfully, and with little or no modification, to processing data from different modalities and application areas.
-
Bootstrapped Learning (BL)
-
Program Manager:
+ -
Mission:
-
The Bootstrapped Learning program seeks to make instructable computing a reality. The "electronic student" will learn from a human teacher who uses spoken language, gestures, demonstration, and many other methods one would find in a human mentored relationship. Furthermore, it will build upon learned concepts and apply that knowledge across different fields of study.
Embedding BL technology in computing systems will eliminate the need for trained programmers in many practical settings, significantly accelerating human-machine instruction, and making possible on-the-fly upgrades by domain experts rather than computer experts. Target applications include a variety of field-trainable military systems, such as human-instructable unmanned aerial vehicles. However, BL technology is being developed and tested against a portfolio of training tasks across very diverse domains, thus it can be applied to any programmable, automated system. As such systems have become ubiquitous, and their operation inaccessible to the layperson, there is also the strong prospect of societal adoption and benefit.
-
Vision:
-
Deep Green is a next-generation, commander-centered battle command and decision support technology that interleaves anticipatory planning with adaptive execution to help the commander think ahead, identify when a plan is going awry, and prepare options - before they are needed.
Approach:
-
Effective battlespace representations for Deep Green must enable practical and tractable reasoning by software agents. In particular, the generation of a state-space representation from current operational data is particularly challenging. Deep Green must be able to use data and information fusion to dynamically create and update representations of the current battle space. Deep Green will then use these representations to predict the "trajectory" of the operation and inform the commander of impending decision points, parts of the plan that need additional options generated, and parts of the plan that are no longer feasible.
Deep Green will involve the use of software agents to analyze the current operation against the plan and to look far ahead in time for the commander to create possible courses of action. These "execution monitors" must be capable of reasoning over the state space to evaluate the actions of the various participants, evaluate the utility and likelihood of actions, and prune the state space representation where possible. Most of this kind of agent technology has proven effective in constrained problem spaces, but must be hardened and scaled to support a real battlespace.
Finally learning algorithms must be developed and enhanced to allow Deep Green to become a better predictor over time. Technologies such as linguistic geometry and episodic memory must be employed to create robust learning algorithms suited for battlefield use. Many of these technologies must be extended to encompass the intractable nature of the modern battlefield as they have been demonstrated in more "well behaved" domains. The domain for Deep Blue, the game of chess, for instance, is well known, the interactions are unambiguously defined, the consequences of any single action are deterministic, etc.
The basic system architecture is comprised of the Commander's Associate (with three sub-components, the Sketch to Plan, Automated Options Generation, and the Sketch to Decide), SimPath, and Crystal Ball, as shown in the figure below.
Sketch to Plan:
-
The Commander's Associate has two major sub-components, Sketch to Plan and Sketch to Decide. Commander's Associate will automatically convert the commander's hand-drawn sketch with accompanying speech of his intent into a Course of Action (COA) at the brigade level. The Commander's Associate must facilitate option generation, "what-if" drills, and rapid decision making. In addition, the Commander's Associate will present information to the commander in a way that aids in battlefield visualization and cognition.
+ - Yellow Pilot
- + -
HSCB
-
CAPABILITIES
-
HSCB programs are organized into four capabilities, each set feeding into the next and forming a cycle.
+ --
Understand
Understand sociocultural parameters of operational environment.
-
Capabilities to support thorough perception and comprehension, grounded in social and behavioral science, of the sociocultural features and dynamics in an operational environment.
The cycle begins with the need to frame the sociocultural structure and dynamics of behavior in a given operational context. To understand at this level means bringing sociocultural theory and concepts to bear to identify the sociocultural features of the terrain that are important to monitor. Understanding is not a single event, and users may constantly need to adapt the initially-applied theories, concepts, and consequent features based on the results of detecting, forecasting, and mitigation. This then initiates a new cycle. This step spans all levels - tactical, operational, and strategic. It requires applied social and behavioral science theory, access to baseline sociocultural data for any given region, descriptive models, and linguistic and sociocultural training.
-
Detect
Detect valid sociocultural behavior signals from noise.
-
Capabilities to discover, distinguish, and locate operationally relevant sociocultural signatures through the collection, processing, and analysis of sociocultural behavior data.
Once the defining features of the sociocultural setting are understood, the next steps are to develop a persistent capability to detect sociocultural behavior signals of interest amidst complexity and noise, and to harvest data for analysis. This entails capabilities for ISR in the area of sociocultural behavior (referred to here as a "social radar"), with particular focus on the challenges associated with open source data collection. It also requires robust systems for storing and managing that data, and tools enabling timely, dynamic analysis.
-
Forecast
Forecast behaviors in response to possible COAs.
-
Capabilities for tracking and forecasting change in entities and phenomena of interest along multiple dimensions (time, space, social networks, types of behavior, etc.) through persistent sensing and modeling of the environment.
Armed with historical and real-time data, users can take the next step: to forecast alternative plausible futures by extrapolating from the collected data. The goals are to identify the various paths that behaviors of interest could take, and to estimate the consequences of each for populations of interest. Among the most important needs in this step are large amounts of data, multidisciplinary theory, and hybrid modeling.
-
Mitigate
Mitigate behaviors and measure effects.
-
Capabilities to develop, prioritize, execute, and measure COAs grounded in the social and behavioral sciences.
The final step in the cycle is to develop and measure the effects of alternative COAs for achieving desired changes. This step builds on all the foregoing ones, and should assist in updating U.S. forces' understanding of the sociocultural behavior terrain, thus continuing the cycle. This step requires education in the use of models for robust decision making, strategic-level theory, integrated systems, decision space visualization, and agile data collection.
OTHER SOCIOCULTURAL PROGRAMS
Minerva
Strategic Multi-Layer Assessment (SMA)
National Science Foundation's Directorate for Social, Behavioral and Economic Sciences
Air Force Office of Scientific Research Collective Behavior and Socio-Cultural Modeling
Air Force Research Laboratory Human Effectiveness Directorate (RH)
- Anticipate and Influence Behavior Division
- National Operational Environment Model
U.S. Army Corps of Engineers (USACE)
- Army Geospatial Center (AGC)
- Measuring Progress in Conflict Environments (MPICE)
U.S. Army Research Institute for the Behavioral and Social Sciences (ARI) Learning and Operating in Culturally Unfamiliar Settings (LOCUS)
U.S. Army Research Laboratory (ARL)
- Human Research and Engineering Directorate
- Network Science Collaborative Technology Alliance
U.S. Army Training and Doctrine Command (TRADOC)
- Cultural Knowledge Consortium (CKC)
- Human Terrain System
Office of Naval Research (ONR) Affordable Human Behavior Modeling (AHBM)
-
Understand
- Syria
~ https://www.facebook.com/permalink.php?story_fbid=1030388917000681&id=658176844221892 + -
In June 2014, ISIL had at least 4,000 fighters in Iraq, and the CIA estimated in September 2014 that it had 20,000–31,500 fighters in Iraq and Syria. The Syrian Observatory for Human Rights estimates that the force numbers around 80,000–100,000 total (up to 50,000 in Syria and 30,000 in Iraq).-
Military activity of ISIL - Wikipedia, the free encyclopedia
-
- + - Somalia
- + - Nigeria
- + - Bangladesh
Process
-
-
- + -
HSCB
Commander's Associate:
-
This component provides the commander the ability to generate quickly qualitative, coarse-grained COA sketches that the computer can interpret. Sketch to Plan will be multi-modal (both sketching and speech) and interactive. The computer will watch the sketch being drawn and listen for key words that indicate sequence, time, intent, etc. as the commander is creating the sketch. Sketch to Plan will induce both a plan and the commander's intent from the sketch and speech. The Sketch to Plan component must be imbued with enough domain knowledge that it knows what it doesn't know and can ask the user a small set of clarifying questions until it understands the sketch and can use it to initialize a combat model. Finally, the dialog generator helps Sketch to Plan understand the commander's option by formulating clarifying questions when necessary.
~ http://zephyr9673.tripod.com/class/I%20pilot%20two.html+ - i
- + - ~ 1 History
- + -
Strong AI
+ - i
- ~ artificial intelligence
- ~ intelligence
- ~ [1]
- ~ artificial intelligence
- ~ science fiction
- ~ futurists
- ~ [2]
- ~ [3]
- ~ Science fiction
- ~ consciousness
- ~ sentience
- ~ sapience
- ~ self-awareness
- ~ applied AI
- ~ [4]
- ~ [1]
- ~ [5]
- ~ problem solving
- ~ reasoning
Strong AI is artificial intelligence that matches or exceeds human intelligence — the intelligence of a machine that can successfully perform any intellectual task that a human being can.[1] It is a primary goal of artificial intelligence research and an important topic for science fiction writers and futurists. Strong AI is also referred to as "artificial general intelligence"[2] or as the ability to perform "general intelligent action".[3] Science fiction associates strong AI with such human traits as consciousness, sentience, sapience and self-awareness.
Some references emphasize a distinction between strong AI and "applied AI"[4] (also called "narrow AI"[1] or "weak AI"[5]): the use of software to study or accomplish specific problem solving or reasoning tasks that do not encompass (or in some cases are completely outside of) the full range of human cognitive abilities.
- ~ 7 Philosophy
- + - ~ 8 Prediction
- + - ~ 4 Tools
- + -
Contents
- + -
1 History
-
Web Directories, Dictionaries and Encyclopedias
-
BotSpot
What's a Bot?
In short: A bot is a software tool for digging through data. You give a bot directions and it bring back answers. The word is short for robot of course, which is derived from the Czech word robota meaning work.
The idea of robots as humanoid machines was first introduced in Karel Capek's 1921 play "R.U.R.," where the playwright conceived Rossum's Universal Robots. Sci-fi writer Isaac Asimov made them famous, beginning with his story I, Robot (1950) and continuing through a string of books known as the Robot Series (see the Isaac Asimov FAQ - for more details including "The Three Laws of Robotics"). - Easily Amused dot com Welcome o' yee of short attention span. Presented here is a collected list of web sites which I found amusing. Although my opinion will vary greatly from yours I hope that you find the majority of these sites at least worth the mouse click to access them.
- Wikipedia A.L.I.C.E. (Artificial Linguistic Internet Computer Entity) is an award-winning natural language processing chatterbot . a program that engages in a conversation with a human by applying some heuristical pattern matching rules to the human's input. It was inspired by Joseph Weizenbaum's classical ELIZA program but takes a quite different approach. It is one of the strongest programs of its type and has won the Loebner Prize three times (in 2000, 2001 and 2004).
- Agentland.com Alice (Artificial Linguistic Internet Computer Entity) is a natural language interface to a telerobot eye. Alice tries ironically to be a computer, so her replies may make some sense but in reality Alice is nothing more than a gigantic pattern-matching case-statement. Remarkably however this elaborate hoax has produced some of the most convincing natural conversations between computer andx humans yet observed.
- Open Directory Chatterbots: ALICE Computers: Artificial Intelligence: Natural Language: Chatterbots: ALICE
- AAAI AI Ethics Any sci-fi buff knows that when computers become self-aware, they ultimately destroy their creators. From 2001: A Space Odyssey to Terminator, the message is clear: The only good self-aware machine is an unplugged one. We may soon find out whether that's true. ... But what about HAL 9000 and the other fictional computers that have run amok?
- American Association for Artificial Intelligence A.I. topics -- Natural LanguageThe value to our society of being able to communicate with computers in everyday "natural" language cannot be overstated. Imagine asking your computer "Does this candidate have a good record on the environment?" or "When is the next televised National League baseball game?" Or being able to tell your PC "Please format my homework the way my English professor likes it".
- American Association for Artificial Intelligence A.I. topics -- The Turing TestAlan Turing proposed an operational test of intelligence as a replacement for the philosophical question, "Can machines think?" Variations of this test have been used to assess performance levels of many AI programs. A restricted adaptation of the Turing Test popularized by the Loebner Competition has been fun, although currently many AI scientists criticize the restricted version of the test because it does not provide insights into the mechanisms of thought.
- www.cs.um.edu.mt/~mros/nlp/ NLP Resource Page
- members.aol.com/lshauser/aiothers.html AI & Other Minds by Larry Hauser.
- www.faqs.org/faqs/ai-faq/general/part6/ Artificial Intelligence FAQ: Open Source AI Software "Chatbots: AI: There is a much maligned chatbot at the Warner Brothers page on the AI movie."
- Sitereview.org A.L.I.C.E is an "Artificial Linguistic Internet Computer Entity" capable of intelligent conversation. She will amaze you with her ability to come up with a relevant response to just about anything! If I didn't know better, I'd think she was human.
- You can become a Botmaster A chat robot is a program that attempts to simulate the conversation or "chat" of a human being. The Chat robot "Eliza" was a well-known early attempt at creating programs that could at least temporarily fool a real human being into thinking they were talking to another person. It is a kind of artificial intelligence.
- Micromegas IA / AI programmes/langages ALICE - Open source natural language artificial intelligence chat robot
-
BotSpot
-
- + -
2 Problems
- 2.1 Deduction, reasoning, problem solving
- 2.2 Knowledge representation
- 2.3 Planning
- 2.4 Learning
- 2.5 Natural language processing
- 2.6 Motion and manipulation
- 2.7 Perception
- 2.8 Social intelligence
- 2.9 Creativity
- 2.10 General intelligence
- + -
3 Approaches
- 3.1 Cybernetics and brain simulation
- 3.2 Symbolic
- 3.3 Sub-symbolic
- 3.4 Statistical
- 3.5 Integrating the approaches
- + -
4 Tools
- 4.1 Search and optimization
- 4.2 Logic
- 4.3 Probabilistic methods for uncertain reasoning
- 4.4 Classifiers and statistical learning methods
- 4.5 Neural networks
- 4.6 Control theory
- 4.7 Languages
- 5 Evaluating progress
- + -
6 Applications
- 6.1 Competitions and prizes
- 6.2 Platforms
- 7 Philosophy
- 8 Prediction
- 9 See also
- + -
10 References
- 10.1 AI textbooks
- 10.2 History of AI
- 10.3 Other sources
- 11 Further reading
- 12 External links
- + -
1 History
- + - i
- ~ Sgp
- ~
- ~ Trajectory
- ~ Tasking
- ~ Crystal
- i
- ~ Chat with A.L.I.C.E.
- ~ Chat with GOD
- ~ What is AIML?
- ~ Bot Industry Survey
- ~ AIML Overview
- ~ Foundation Bot Directory
- + -
i
- ~ Effect size
- + -
Form may also refer to:
- Form, a shallow depression or flattened nest of grass used by a hare
- Form (document), a document (printed or electronic) with spaces in which to write or enter data
- Form (education), a class, set or group of students
- Form (exercise), a proper way of performing an exercise
- Form (horse racing), a record of a racehorse's performance, or similarly for an athlete
- Form, a criminal record
- Form, a font designed by Aldo Novarese (1966)
- Form (religion), an academic term for prescriptions or norms on religious practice
- Musical form, a generic type of composition or the structure of a particular piece
- FORM, an American architecture magazine
- + -
Biology:
- Form (botany), a formal taxon at a rank lower than species
- Form (zoology), informal taxa used sometimes in zoology
- + -
Computing:
- Form (web), a document form used on a web page to, typically, submit user data to a server
- Form (programming), a component-based representation of a GUI window
- FORM (symbolic manipulation system), a program for symbolic computations
- Form (computer virus), the most common computer virus of the 1990s
- Oracle Forms, a Rapid Application Development environment for developing database applications
- Windows Forms
- XForms, an XML format for the specification of user interfaces, specifically web forms
- Trapcode Form, a motion graphic editing plug-in from Red Giant Software
- + -
Martial arts:
- Kata (型 or 形), the detailed pattern of defence-and-attack
- Taeguk (Taekwondo) (형), the "forms" used to create a foundation for the teaching of Taekwondo
- Taolu (套路), forms used in Chinese martial arts and sport wushu
- + -
Mathematics:
Algebraic form (homogeneous polynomial), which generalises quadratic forms to degrees 3 and more, also known as quantics or simply forms
Bilinear form, on a vector space V over a field F is a mapping V × V → F that is linear in both arguments
Differential form, a concept from differential topology that combines multi linear forms and smooth functions
Indeterminate form, an algebraic expression that cannot be used to evaluate a limit
Modular form, a (complex) analytic function on the upper half plane satisfying a certain kind of functional equation and growth condition
Multilinear form, which generalises bilinear forms to mappings VN → F
Quadratic form, a homogeneous polynomial of degree two in a number of variables
- + -
Philosophy:
Substantial form
Theory of Forms
Value-form, an approach to understanding the origins of commodity trade and the formation of markets.
- + -
See also
- Formwork, a mould used for concrete construction
- Isoform, several different forms of the same protein
- Sixth form, an English term for the final two years of secondary school
- The Forms (band), an American indie rock band
- Formation (disambiguation)
- Formula (disambiguation)
- Conformity (disambiguation)
- Deformation (disambiguation)
- Inform (disambiguation)
- Reform (disambiguation)
- All pages beginning with "Form"
- All pages with titles containing "Form"
- + -
Form may also refer to:
- Form refers to the shape, visual appearance, or configuration of an object.
- ~ shape
- ~ visual appearance
- ~ configuration
- ~ hare
- ~ Form (document)
- ~ Form (education)
- ~ Form (exercise)
- ~ Form (horse racing)
- ~ criminal record
- ~ Aldo Novarese
- ~ Form (religion)
- ~ Musical form
- ~ FORM
- ~ Form (botany)
- ~ Form (zoology)
- ~ Form (web)
- ~ Form (programming)
- ~ FORM (symbolic manipulation system)
- ~ Form (computer virus)
- ~ Oracle Forms
- ~ Windows Forms
- ~ XForms
- ~ Red Giant Software
- ~ Kata
- ~ Taeguk (Taekwondo)
- ~ Taolu
- ~ homogeneous polynomial
- ~ Bilinear form
- ~ Differential form
- ~ Indeterminate form
- ~ Modular form
- ~ Multilinear form
- ~ Quadratic form
- ~ Substantial form
- ~ Theory of Forms
- ~ Value-form
- ~ edit
- ~ Formwork
- ~ Isoform
- ~ Sixth form
- ~ The Forms (band)
- ~ Formation (disambiguation)
- ~ Formula (disambiguation)
- ~ Conformity (disambiguation)
- ~ Deformation (disambiguation)
- ~ Inform (disambiguation)
- ~ Reform (disambiguation)
- ~ All pages beginning with "Form"
- ~ All pages with titles containing "Form"
- ~ Effect size
- + -
i
- ~ result
- ~ List of effects
- ~ causality
- ~ Drug effect
- ~ Therapeutic effect
- ~ Adverse effect
- ~ dose-response curve
- ~ Special effect
- ~ Sound effect
- ~ Effects unit
- ~ Effects pedal
- ~ Visual effects
- ~ personal property
- ~ All pages beginning with "Effect"
- ~ All pages with titles containing "Effect"
- ~ Affect (disambiguation)
- ~ Effectiveness (disambiguation)
- ~ Efficacy
- ~ Pragmatism
- ~ Corrective strategem
- ~ Artificial Intelligence
- ~
NELL: Never-Ending Language Learning
~ computervisiononline.com > Blog > Never-ending-image-learner
Brain-inspired
- ~ https://code.google.com/p/ahuman/
- ~ en.wikipedia.org > Wiki > Blue Brain Project
- ~ andcorporation.com
- ~ numenta.org > Nupic
- ~ vicarious.com
- ~ tinmansystems.com
- ~ aileenn.com
-
Cognitive architectures
- ~
Automated Option Generation:
-
The focus of Deep Green is on tools to help the commander (and staff) generate options quickly. Leaders from the field generally do not want machine-generated courses of action. Nevertheless, under Deep Green, we intend to sponsor a small set of modest efforts to generate options automatically. The long-term vision of Deep Green is for options to be generated by both the commander and the computer. This highlights the need for Sketch to Plan to induce the commander's intent from the free-hand sketches. Any options generated by the computer should feasibly meet the commander's intent.
+ -
-
APP-6ASymbol Name Strength Constituent units Commander or leader XXXXXX region, theater 1,000,000+ 4+ army groups general, army general, five star general or field marshal XXXXX army group, front 250,000+ 2+ armies general, army general, five star general or field marshal XXXX army 60,000–100,000+ 2–4 corps general, army general, four star general or colonel general XXX corps 30,000–80,000 2+ divisions lieutenant general, corps general or three star general XX division 10,000–20,000 2–4 brigades or regiments major general, divisional general or two star general X brigade 2000–5000 2+ regiments, 3–6 battalions or Commonwealth regiments brigadier general, brigade general, or one star general(sometimes colonel) III regiment or group 2000–3000 2+ battalions or U.S. Cavalry squadrons colonel II infantry battalion, U.S. Cavalry squadron, or Commonwealth armoured regiment 300–1000 2–6 companies, batteries, U.S. Cavalry troops, or Commonwealth squadrons lieutenant colonel I infantry company, artillery battery, U.S. Cavalrytroop, or Commonwealth armour or combat engineering squadron 70–250 2–8 platoons or Commonwealth troops chief warrant officer, captain ormajor ••• platoon or Commonwealth troop 25–60 2+ squads, sections, or vehicles warrant officer, first or secondlieutenant •• section or patrol 8–12 2+ fireteams corporal to sergeant • squad or crew 8–16 2+ fireteams or 1+ cell corporal to staff sergeant Ø fireteam 4–5 n/a lance corporal to sergeant Ø fire and maneuver team 2 n/a any/private first class
+ -
- + -
+ -XXXXXX
+ -XXXXX
+ -XXXX
+ -XXX
+ -XX X + -
- + -
- + -
- + -
- + -
- + -
Ø -
fireteam 4–5 n/a lance corporal to sergeant
Ø -
fire and maneuver team 2 n/a any/private first class
-
- + -
+ -
- + -
III -
regiment or group
+ -II I -
infantry company, artillery battery, U.S. Cavalrytroop, or Commonwealth armour or combat engineering squadron
+ -
- + -
- + -
- + -
- + -
- + -
Ø -
fireteam 4–5 n/a lance corporal to sergeant
Ø -
fire and maneuver team 2 n/a any/private first class
-
- + -
-
+ -
- + -
+ -•••
+ -•• • -
squad or crew
+ -
- + -
- + -
- + -
- + -
- + -
Ø -
fireteam 4–5 n/a lance corporal to sergeant
Ø -
fire and maneuver team 2 n/a any/private first class
-
- + -
-
+ -
- + -
Ø -
fireteam 4–5 n/a lance corporal to sergeant
Ø -
fire and maneuver team 2 n/a any/private first class
+ -
- + -
- + -
- + -
- + -
- + -
Ø -
fireteam 4–5 n/a lance corporal to sergeant
Ø -
fire and maneuver team 2 n/a any/private first class
-
- + -
-
- + -
- + -
- + -
- + -
- + -
Ø -
fireteam 4–5 n/a lance corporal to sergeant
Ø -
fire and maneuver team 2 n/a any/private first class
-
- + -
-
- Collective action, the provision of public goods through collaboration
- Direct action, an instance of political activism
- Group action in mathematics
- Lawsuit, sometimes called a civil action and actio
- Military action (combat), a scale of combat within the hierarchy of combat
- Social actions, which take into account actions and reactions of other individuals
- Strike action, a deliberate absence from work
Sketch to Decide:
-
When the commander is asked for a decision, Sketch to Decide will allow him/her to explore the future space to gain an appreciation for the ramifications of a choice. Sketch to Decide is designed to allow the user to "see the future," but this capability must be developed with care to prevent confusing the decision space. The abstract nature of the state and the uncertainty of predictions, locations of units, etc. must be portrayed intuitively. At any "frame" in the Sketch to Decide graph, the user can perform Sketch to Plan actions, allowing the commander to conduct "what-if" drills wherever he wants in the future space. By presenting decisions early and allowing the commander to explore the future space, Sketch to Decide supports adaptive execution, allowing the commander to make decisions when they are needed, rather than committing too early.
- + -
- + -
+ -XXXXXX
+ -XXXXX
+ -XXXX
+ -XXX
+ -XX X
- + -
- + -
- + -
- + -
- + -
Ø -
fireteam 4–5 n/a lance corporal to sergeant
Ø -
fire and maneuver team 2 n/a any/private first class
-
- + -
- + -
SimPath:
-
SimPath is the simulation component of Deep Green. It is used to generate the possible futures that result from a set of plans (one plan for each side/force in the operation). Besides being very fast, SimPath is designed to generate a broad set of possible futures. These futures should be feasible, even if not expected by human users. Over time, SimPath should learn to be a better predictor of possible futures, based on presented options. SimPath identifies branch points, predicts the range of possible outcomes, predicts the likelihood of each outcome, and then continues to simulate along each path/trajectory. This will require an innovative hybrid of qualitative and quantitative technologies.
~ https://zephyr46.tripod.com/classes/trajectory.html
Crystal Ball:
-
During pre-operations planning, Crystal Ball receives options from Sketch to Plan for all sides and forces. Crystal ball assembles the permutations of plans and sends them to SimPath to generate the possible futures that result from each permutation. SimPath returns sub-graphs of possible futures and branch points to Crystal Ball with annotations as to SimPath's a priori estimate of the likelihood of these options. Another function of Crystal Ball is to merge these sub-graphs so the futures that are qualitatively the same (regardless of which permutation of options generated them) are combined. Once the operation is underway, Crystal Ball will get information about the ongoing operation from the battle command systems. Crystal Ball uses this information about the current operation to update the likelihood estimates of the many possible futures. Having done that, Crystal Ball can compare the likelihood, utility, and flexibility and estimate which futures are likely to occur that have little value or flexibility. Crystal Ball will use this estimate to nominate to the commander futures at which he/she should focus some planning effort to build additional options/branches. If the commander reaches a future for which no options have been developed, he/she has been surprised and the enemy is now operating inside his/her decision cycle. Crystal Ball will also use this information and additional heuristics to nominate futures for pruning from the graph and to identify decision points to send to Sketch to Decide. Pruning, however, will not be based purely on likelihood, but also on attributes such as risk to the operation.
- ~
http://www.darpa.mil/ipto/programs/dg/dg.asp
~
http://www.defenseindustrydaily.com/files/PUB_BAA_DARPA_07-56_Deep_Green.pdf
+ - Spectrum
- ~ Blue Pilot
- ~ Red Pilot
- ~ Orange Pilot
- ~ White Pilot
- + -
Yellow Pilot
- HSCB
-
CAPABILITIES
-
HSCB programs are organized into four capabilities, each set feeding into the next and forming a cycle.
+ --
Understand
Understand sociocultural parameters of operational environment.
-
Capabilities to support thorough perception and comprehension, grounded in social and behavioral science, of the sociocultural features and dynamics in an operational environment.
The cycle begins with the need to frame the sociocultural structure and dynamics of behavior in a given operational context. To understand at this level means bringing sociocultural theory and concepts to bear to identify the sociocultural features of the terrain that are important to monitor. Understanding is not a single event, and users may constantly need to adapt the initially-applied theories, concepts, and consequent features based on the results of detecting, forecasting, and mitigation. This then initiates a new cycle. This step spans all levels - tactical, operational, and strategic. It requires applied social and behavioral science theory, access to baseline sociocultural data for any given region, descriptive models, and linguistic and sociocultural training.
-
Detect
Detect valid sociocultural behavior signals from noise.
-
Capabilities to discover, distinguish, and locate operationally relevant sociocultural signatures through the collection, processing, and analysis of sociocultural behavior data.
Once the defining features of the sociocultural setting are understood, the next steps are to develop a persistent capability to detect sociocultural behavior signals of interest amidst complexity and noise, and to harvest data for analysis. This entails capabilities for ISR in the area of sociocultural behavior (referred to here as a "social radar"), with particular focus on the challenges associated with open source data collection. It also requires robust systems for storing and managing that data, and tools enabling timely, dynamic analysis.
-
Forecast
Forecast behaviors in response to possible COAs.
-
Capabilities for tracking and forecasting change in entities and phenomena of interest along multiple dimensions (time, space, social networks, types of behavior, etc.) through persistent sensing and modeling of the environment.
Armed with historical and real-time data, users can take the next step: to forecast alternative plausible futures by extrapolating from the collected data. The goals are to identify the various paths that behaviors of interest could take, and to estimate the consequences of each for populations of interest. Among the most important needs in this step are large amounts of data, multidisciplinary theory, and hybrid modeling.
-
Mitigate
Mitigate behaviors and measure effects.
-
Capabilities to develop, prioritize, execute, and measure COAs grounded in the social and behavioral sciences.
The final step in the cycle is to develop and measure the effects of alternative COAs for achieving desired changes. This step builds on all the foregoing ones, and should assist in updating U.S. forces' understanding of the sociocultural behavior terrain, thus continuing the cycle. This step requires education in the use of models for robust decision making, strategic-level theory, integrated systems, decision space visualization, and agile data collection.
OTHER SOCIOCULTURAL PROGRAMS
Minerva
Strategic Multi-Layer Assessment (SMA)
National Science Foundation's Directorate for Social, Behavioral and Economic Sciences
Air Force Office of Scientific Research Collective Behavior and Socio-Cultural Modeling
Air Force Research Laboratory Human Effectiveness Directorate (RH)
- Anticipate and Influence Behavior Division
- National Operational Environment Model
U.S. Army Corps of Engineers (USACE)
- Army Geospatial Center (AGC)
- Measuring Progress in Conflict Environments (MPICE)
U.S. Army Research Institute for the Behavioral and Social Sciences (ARI) Learning and Operating in Culturally Unfamiliar Settings (LOCUS)
U.S. Army Research Laboratory (ARL)
- Human Research and Engineering Directorate
- Network Science Collaborative Technology Alliance
U.S. Army Training and Doctrine Command (TRADOC)
- Cultural Knowledge Consortium (CKC)
- Human Terrain System
Office of Naval Research (ONR) Affordable Human Behavior Modeling (AHBM)
-
Understand
Test areas
- + - Syria
- + - Somalia
- + - Nigeria
- + - Bangladesh
Process
-
-
- HSCB
- ~ Green Pilot
-
- Indigo
- Archive
- ~ https://web.archive.org/web/20130219055023/https://zephyr46.tripod.com/fynderpresponse/
- ~ https://web.archive.org/web/20130104051236/https://zephyr46.tripod.com/salt/id11.html
- ~ https://web.archive.org/web/20130104051213/https://zephyr46.tripod.com/salt/
- Earthbank
- ~ https://web.archive.org/web/20130219055004/https://zephyr46.tripod.com/fynderpresponse/id12.html
- + -
~ Orders of magnitude
~ Orders of magnitude (length)
~ Visualisation + - ~
- ~ 20th century
- ~ Periodization
- ~ Planck_time
- ~ Time (Orders of magnitude)
- yoctosecond zeptosecond
- ~ Attosecond
- ~ Femtosecond
- ~ Picosecond
- ~ Nanosecond
- ~ Microsecond
- ~ Millisecond
- ~ Second
- + -
~ Minute
- ~ Utopia
- ~ List of freedom indices
- ~ Homeostasis
-
DirectionologyMilky Way and Andromeda galaxy are approaching each other with a speed of about 130 km/s, however the collision of these two galaxies will not occur for about 5 billion years (AstroFile). Another result I found was that our galaxy and neighbors are moving at 600 km/s in the direction of the constellation Hydra (Scientific American). Finally, I found that the Milky Way moves through space within the cluster of galaxies it is a member of, and this cluster in turn moves through space towards yet another larger cluster of galaxies off in the direction of the constellation Virgo. This speed is approximately 300 km/s (Ask the Space Scientist). Therefore, the speed of the Milky Way galaxy is not a single number, its value is relative to the speed of other objects.Survey effects of scale motions with pioneer and voyager type robots, effects of gravity over distence. Probes targeted towards and opposition, to measure velocities and resistences.Andromeda_GalaxyVirgo_supercluster
Since the late 1980s it has been apparent that not only the Local Group, but all matter out to a distance of at least 50 Mpc is experiencing a bulk flow on the order of 600 km/sec in the direction of the Norma cluster (Abell 3627).[10] Lynden-Bell et al. (1988) dubbed the cause of this "The Great Attractor." While astronomers are confident of the velocity of the LS, which has been measured against the Cosmic Microwave Background (CMB), the nature of what is causing it remains poorly understood.
-
- ~ Intersectionality
- ~ Conflict
- ~ Dystopia
- ~ 21st century
- ~ Kilosecond
- ~ Hour
- ~ Megasecond
- 11.6 days
- ~ Gigasecond
- 31.558 years
- ~ 22nd century
- ~ Terasecond and longer
-
Teraseconds
-
Petaseconds
-
Exaseconds
-
Zettaseconds
-
Yottaseconds
-
- megametre
- terametre
- petametre
- Archive
- Sense
- Calabration
- Indigo
- ~ Effect size
- ~ Trajectory
- ~ Homeostasis
- ~ Intersectionality
- ~ Conflict
- ~ Dystopia
- ~ 2016
- ~ 2017
- ~ 2018
- ~ 2019
- ~ 2020s
- ~ 2030s
- ~ 2040s
- ~ Minute
- ~ Kilosecond
- ~ Hour
- ~ Megasecond
- 11.6 days
- ~ Gigasecond
- 31.558 years
- ~ 22nd century
- + -
~ Terasecond and longer
-
Teraseconds
-
Petaseconds
-
Exaseconds
-
Zettaseconds
-
Yottaseconds
-
- ~ 2016
-
- January
-
+ -
-
APP-6ASymbol Name Strength Constituent units Commander or leader XXXXXX region, theater 1,000,000+ 4+ army groups general, army general, five star general or field marshal XXXXX army group, front 250,000+ 2+ armies general, army general, five star general or field marshal XXXX army 60,000–100,000+ 2–4 corps general, army general, four star general or colonel general XXX corps 30,000–80,000 2+ divisions lieutenant general, corps general or three star general XX division 10,000–20,000 2–4 brigades or regiments major general, divisional general or two star general X brigade 2000–5000 2+ regiments, 3–6 battalions or Commonwealth regiments brigadier general, brigade general, or one star general(sometimes colonel) III regiment or group 2000–3000 2+ battalions or U.S. Cavalry squadrons colonel II infantry battalion, U.S. Cavalry squadron, or Commonwealth armoured regiment 300–1000 2–6 companies, batteries, U.S. Cavalry troops, or Commonwealth squadrons lieutenant colonel I infantry company, artillery battery, U.S. Cavalrytroop, or Commonwealth armour or combat engineering squadron 70–250 2–8 platoons or Commonwealth troops chief warrant officer, captain ormajor ••• platoon or Commonwealth troop 25–60 2+ squads, sections, or vehicles warrant officer, first or secondlieutenant •• section or patrol 8–12 2+ fireteams corporal to sergeant • squad or crew 8–16 2+ fireteams or 1+ cell corporal to staff sergeant Ø fireteam 4–5 n/a lance corporal to sergeant Ø fire and maneuver team 2 n/a any/private first class
+ -
- + -
+ -XXXXXX
+ -XXXXX
+ -XXXX
+ -XXX
+ -XX X + -
- + -
- + -
- + -
- + -
- + -
Ø -
fireteam 4–5 n/a lance corporal to sergeant
Ø -
fire and maneuver team 2 n/a any/private first class
-
- + -
+ -
- + -
III -
regiment or group
+ -II I -
infantry company, artillery battery, U.S. Cavalrytroop, or Commonwealth armour or combat engineering squadron
+ -
- + -
- + -
- + -
- + -
- + -
Ø -
fireteam 4–5 n/a lance corporal to sergeant
Ø -
fire and maneuver team 2 n/a any/private first class
-
- + -
-
+ -
- + -
+ -•••
+ -•• • -
squad or crew
+ -
- + -
- + -
- + -
- + -
- + -
Ø -
fireteam 4–5 n/a lance corporal to sergeant
Ø -
fire and maneuver team 2 n/a any/private first class
-
- + -
-
+ -
- + -
Ø -
fireteam 4–5 n/a lance corporal to sergeant
Ø -
fire and maneuver team 2 n/a any/private first class
+ -
- + -
- + -
- + -
- + -
- + -
Ø -
fireteam 4–5 n/a lance corporal to sergeant
Ø -
fire and maneuver team 2 n/a any/private first class
-
- + -
-
- + -
- + -
- + -
- + -
- + -
Ø -
fireteam 4–5 n/a lance corporal to sergeant
Ø -
fire and maneuver team 2 n/a any/private first class
-
- + -
-
-
- Febuary
- March
- April
- May
- June
- July
- August
- September
- October
- November
- December
- January
-
- ~ 2017
- + -
- January
- Febuary
- March
- April
- May
- June
- July
- August
- September
- October
- November
- December
- + -
- ~ 2018
- + -
- January
- Febuary
- March
- April
- May
- June
- July
- August
- September
- October
- November
- December
- + -
- ~ 2019
- + -
- January
- Febuary
- March
- April
- May
- June
- July
- August
- September
- October
- November
- December
- + -
- ~ 2020s
- ~ 2030s
- ~ 2040s
- ~ 22nd century
- ~
- + -
SimPath:
-
SimPath is the simulation component of Deep Green. It is used to generate the possible futures that result from a set of plans (one plan for each side/force in the operation). Besides being very fast, SimPath is designed to generate a broad set of possible futures. These futures should be feasible, even if not expected by human users. Over time, SimPath should learn to be a better predictor of possible futures, based on presented options. SimPath identifies branch points, predicts the range of possible outcomes, predicts the likelihood of each outcome, and then continues to simulate along each path/trajectory. This will require an innovative hybrid of qualitative and quantitative technologies.
~ https://zephyr46.tripod.com/classes/trajectory.html
Crystal Ball:
-
During pre-operations planning, Crystal Ball receives options from Sketch to Plan for all sides and forces. Crystal ball assembles the permutations of plans and sends them to SimPath to generate the possible futures that result from each permutation. SimPath returns sub-graphs of possible futures and branch points to Crystal Ball with annotations as to SimPath's a priori estimate of the likelihood of these options. Another function of Crystal Ball is to merge these sub-graphs so the futures that are qualitatively the same (regardless of which permutation of options generated them) are combined. Once the operation is underway, Crystal Ball will get information about the ongoing operation from the battle command systems. Crystal Ball uses this information about the current operation to update the likelihood estimates of the many possible futures. Having done that, Crystal Ball can compare the likelihood, utility, and flexibility and estimate which futures are likely to occur that have little value or flexibility. Crystal Ball will use this estimate to nominate to the commander futures at which he/she should focus some planning effort to build additional options/branches. If the commander reaches a future for which no options have been developed, he/she has been surprised and the enemy is now operating inside his/her decision cycle. Crystal Ball will also use this information and additional heuristics to nominate futures for pruning from the graph and to identify decision points to send to Sketch to Decide. Pruning, however, will not be based purely on likelihood, but also on attributes such as risk to the operation.
- ~
http://www.darpa.mil/ipto/programs/dg/dg.asp
~
http://www.defenseindustrydaily.com/files/PUB_BAA_DARPA_07-56_Deep_Green.pdf
+ - Spectrum
- ~ Blue Pilot
- ~ Red Pilot
- ~ Orange Pilot
- ~ White Pilot
- + -
Yellow Pilot
- HSCB
-
CAPABILITIES
-
HSCB programs are organized into four capabilities, each set feeding into the next and forming a cycle.
+ --
Understand
Understand sociocultural parameters of operational environment.
-
Capabilities to support thorough perception and comprehension, grounded in social and behavioral science, of the sociocultural features and dynamics in an operational environment.
The cycle begins with the need to frame the sociocultural structure and dynamics of behavior in a given operational context. To understand at this level means bringing sociocultural theory and concepts to bear to identify the sociocultural features of the terrain that are important to monitor. Understanding is not a single event, and users may constantly need to adapt the initially-applied theories, concepts, and consequent features based on the results of detecting, forecasting, and mitigation. This then initiates a new cycle. This step spans all levels - tactical, operational, and strategic. It requires applied social and behavioral science theory, access to baseline sociocultural data for any given region, descriptive models, and linguistic and sociocultural training.
-
Detect
Detect valid sociocultural behavior signals from noise.
-
Capabilities to discover, distinguish, and locate operationally relevant sociocultural signatures through the collection, processing, and analysis of sociocultural behavior data.
Once the defining features of the sociocultural setting are understood, the next steps are to develop a persistent capability to detect sociocultural behavior signals of interest amidst complexity and noise, and to harvest data for analysis. This entails capabilities for ISR in the area of sociocultural behavior (referred to here as a "social radar"), with particular focus on the challenges associated with open source data collection. It also requires robust systems for storing and managing that data, and tools enabling timely, dynamic analysis.
-
Forecast
Forecast behaviors in response to possible COAs.
-
Capabilities for tracking and forecasting change in entities and phenomena of interest along multiple dimensions (time, space, social networks, types of behavior, etc.) through persistent sensing and modeling of the environment.
Armed with historical and real-time data, users can take the next step: to forecast alternative plausible futures by extrapolating from the collected data. The goals are to identify the various paths that behaviors of interest could take, and to estimate the consequences of each for populations of interest. Among the most important needs in this step are large amounts of data, multidisciplinary theory, and hybrid modeling.
-
Mitigate
Mitigate behaviors and measure effects.
-
Capabilities to develop, prioritize, execute, and measure COAs grounded in the social and behavioral sciences.
The final step in the cycle is to develop and measure the effects of alternative COAs for achieving desired changes. This step builds on all the foregoing ones, and should assist in updating U.S. forces' understanding of the sociocultural behavior terrain, thus continuing the cycle. This step requires education in the use of models for robust decision making, strategic-level theory, integrated systems, decision space visualization, and agile data collection.
OTHER SOCIOCULTURAL PROGRAMS
Minerva
Strategic Multi-Layer Assessment (SMA)
National Science Foundation's Directorate for Social, Behavioral and Economic Sciences
Air Force Office of Scientific Research Collective Behavior and Socio-Cultural Modeling
Air Force Research Laboratory Human Effectiveness Directorate (RH)
- Anticipate and Influence Behavior Division
- National Operational Environment Model
U.S. Army Corps of Engineers (USACE)
- Army Geospatial Center (AGC)
- Measuring Progress in Conflict Environments (MPICE)
U.S. Army Research Institute for the Behavioral and Social Sciences (ARI) Learning and Operating in Culturally Unfamiliar Settings (LOCUS)
U.S. Army Research Laboratory (ARL)
- Human Research and Engineering Directorate
- Network Science Collaborative Technology Alliance
U.S. Army Training and Doctrine Command (TRADOC)
- Cultural Knowledge Consortium (CKC)
- Human Terrain System
Office of Naval Research (ONR) Affordable Human Behavior Modeling (AHBM)
-
Understand
Test areas
- + - Syria
- + - Somalia
- + - Nigeria
- + - Bangladesh
Process
-
-
- HSCB
- ~ Green Pilot
-
- Indigo
- Archive
- ~ https://web.archive.org/web/20130219055023/https://zephyr46.tripod.com/fynderpresponse/
- ~ https://web.archive.org/web/20130104051236/https://zephyr46.tripod.com/salt/id11.html
- ~ https://web.archive.org/web/20130104051213/https://zephyr46.tripod.com/salt/
- Earthbank
- ~ https://web.archive.org/web/20130219055004/https://zephyr46.tripod.com/fynderpresponse/id12.html
- + -
~ Orders of magnitude
~ Orders of magnitude (length)
~ Visualisation + - ~
- ~ 20th century
- ~ Periodization
- ~ Planck_time
- ~ Time (Orders of magnitude)
- yoctosecond zeptosecond
- ~ Attosecond
- ~ Femtosecond
- ~ Picosecond
- ~ Nanosecond
- ~ Microsecond
- ~ Millisecond
- ~ Second
- + -
~ Minute
- ~ Utopia
- ~ List of freedom indices
- ~ Homeostasis
-
DirectionologyMilky Way and Andromeda galaxy are approaching each other with a speed of about 130 km/s, however the collision of these two galaxies will not occur for about 5 billion years (AstroFile). Another result I found was that our galaxy and neighbors are moving at 600 km/s in the direction of the constellation Hydra (Scientific American). Finally, I found that the Milky Way moves through space within the cluster of galaxies it is a member of, and this cluster in turn moves through space towards yet another larger cluster of galaxies off in the direction of the constellation Virgo. This speed is approximately 300 km/s (Ask the Space Scientist). Therefore, the speed of the Milky Way galaxy is not a single number, its value is relative to the speed of other objects.Survey effects of scale motions with pioneer and voyager type robots, effects of gravity over distence. Probes targeted towards and opposition, to measure velocities and resistences.Andromeda_GalaxyVirgo_supercluster
Since the late 1980s it has been apparent that not only the Local Group, but all matter out to a distance of at least 50 Mpc is experiencing a bulk flow on the order of 600 km/sec in the direction of the Norma cluster (Abell 3627).[10] Lynden-Bell et al. (1988) dubbed the cause of this "The Great Attractor." While astronomers are confident of the velocity of the LS, which has been measured against the Cosmic Microwave Background (CMB), the nature of what is causing it remains poorly understood.
-
- ~ Intersectionality
- ~ Conflict
- ~ Dystopia
- ~ 21st century
- ~ Kilosecond
- ~ Hour
- ~ Megasecond
- 11.6 days
- ~ Gigasecond
- 31.558 years
- ~ 22nd century
- ~ Terasecond and longer
-
Teraseconds
-
Petaseconds
-
Exaseconds
-
Zettaseconds
-
Yottaseconds
-
- megametre
- terametre
- petametre
- Archive
- Sense
- Calabration
- Indigo
- ~ Effect size
- ~ Trajectory
- ~ Homeostasis
- ~ Intersectionality
- ~ Conflict
- ~ Dystopia
- ~ 2016
- ~ 2017
- ~ 2018
- ~ 2019
- ~ 2020s
- ~ 2030s
- ~ 2040s
- ~ Minute
- ~ Kilosecond
-
16 minutes, 40 seconds
-
- ~ Hour
- ~ Megasecond
- 11.6 days
- ~ Gigasecond
- 31.558 years
- ~ 22nd century
- + -
~ Terasecond and longer
-
Teraseconds
-
Petaseconds
-
Exaseconds
-
Zettaseconds
-
Yottaseconds
-
- ~ 2016
- + -
- January
-
+ -
-
APP-6ASymbol Name Strength Constituent units Commander or leader XXXXXX region, theater 1,000,000+ 4+ army groups general, army general, five star general or field marshal XXXXX army group, front 250,000+ 2+ armies general, army general, five star general or field marshal XXXX army 60,000–100,000+ 2–4 corps general, army general, four star general or colonel general XXX corps 30,000–80,000 2+ divisions lieutenant general, corps general or three star general XX division 10,000–20,000 2–4 brigades or regiments major general, divisional general or two star general X brigade 2000–5000 2+ regiments, 3–6 battalions or Commonwealth regiments brigadier general, brigade general, or one star general(sometimes colonel) III regiment or group 2000–3000 2+ battalions or U.S. Cavalry squadrons colonel II infantry battalion, U.S. Cavalry squadron, or Commonwealth armoured regiment 300–1000 2–6 companies, batteries, U.S. Cavalry troops, or Commonwealth squadrons lieutenant colonel I infantry company, artillery battery, U.S. Cavalrytroop, or Commonwealth armour or combat engineering squadron 70–250 2–8 platoons or Commonwealth troops chief warrant officer, captain ormajor ••• platoon or Commonwealth troop 25–60 2+ squads, sections, or vehicles warrant officer, first or secondlieutenant •• section or patrol 8–12 2+ fireteams corporal to sergeant • squad or crew 8–16 2+ fireteams or 1+ cell corporal to staff sergeant Ø fireteam 4–5 n/a lance corporal to sergeant Ø fire and maneuver team 2 n/a any/private first class
+ -
- + -
+ -XXXXXX
+ -XXXXX
+ -XXXX
+ -XXX
+ -XX X + -
- + -
- + -
- + -
- + -
- + -
Ø -
fireteam 4–5 n/a lance corporal to sergeant
Ø -
fire and maneuver team 2 n/a any/private first class
-
- + -
+ -
- + -
III -
regiment or group
+ -II I -
infantry company, artillery battery, U.S. Cavalrytroop, or Commonwealth armour or combat engineering squadron
+ -
- + -
- + -
- + -
- + -
- + -
Ø -
fireteam 4–5 n/a lance corporal to sergeant
Ø -
fire and maneuver team 2 n/a any/private first class
-
- + -
-
+ -
- + -
+ -•••
+ -•• • -
squad or crew
+ -
- + -
- + -
- + -
- + -
- + -
Ø -
fireteam 4–5 n/a lance corporal to sergeant
Ø -
fire and maneuver team 2 n/a any/private first class
-
- + -
-
+ -
- + -
Ø -
fireteam 4–5 n/a lance corporal to sergeant
Ø -
fire and maneuver team 2 n/a any/private first class
+ -
- + -
- + -
- + -
- + -
- + -
Ø -
fireteam 4–5 n/a lance corporal to sergeant
Ø -
fire and maneuver team 2 n/a any/private first class
-
- + -
-
- + -
- + -
- + -
- + -
- + -
Ø -
fireteam 4–5 n/a lance corporal to sergeant
Ø -
fire and maneuver team 2 n/a any/private first class
-
- + -
-
-
- Febuary
- March
- April
- May
- June
- July
- August
- September
- October
- November
- December
- January
- + -
- ~ 2017
- + -
- January
- Febuary
- March
- April
- May
- June
- July
- August
- September
- October
- November
- December
- + -
- ~ 2018
- + -
- January
- Febuary
- March
- April
- May
- June
- July
- August
- September
- October
- November
- December
- + -
- ~ 2019
- + -
- January
- Febuary
- March
- April
- May
- June
- July
- August
- September
- October
- November
- December
- + -
- ~ 2020s
- ~ 2030s
- ~ 2040s
- ~ 22nd century
- ~
- + -
~ Kilosecond
-
16 minutes, 40 seconds
-
- ~ Hour
- ~ Day
- ~ Week
- + -
~ Megasecond
-
11.6 days
-
- ~ Month
- ~ Year
- ~ Decade
- + -
~ Gigasecond
-
31.558 years
-
- ~ Century
- ~ Millennium
- + -
~ Terasecond and longer
-
Teraseconds
-
Petaseconds
-
Exaseconds
-
Zettaseconds
-
Yottaseconds
-
- megametre
- terametre
- petametre
-
Memory management and
resource protectionStorage access and
file systems+ - Fynder
-
היום
- i
- + - ~ 1 History
- + -
Strong AI
+ - i
- ~ artificial intelligence
- ~ intelligence
- ~ [1]
- ~ artificial intelligence
- ~ science fiction
- ~ futurists
- ~ [2]
- ~ [3]
- ~ Science fiction
- ~ consciousness
- ~ sentience
- ~ sapience
- ~ self-awareness
- ~ applied AI
- ~ [4]
- ~ [1]
- ~ [5]
- ~ problem solving
- ~ reasoning
Strong AI is artificial intelligence that matches or exceeds human intelligence — the intelligence of a machine that can successfully perform any intellectual task that a human being can.[1] It is a primary goal of artificial intelligence research and an important topic for science fiction writers and futurists. Strong AI is also referred to as "artificial general intelligence"[2] or as the ability to perform "general intelligent action".[3] Science fiction associates strong AI with such human traits as consciousness, sentience, sapience and self-awareness.
Some references emphasize a distinction between strong AI and "applied AI"[4] (also called "narrow AI"[1] or "weak AI"[5]): the use of software to study or accomplish specific problem solving or reasoning tasks that do not encompass (or in some cases are completely outside of) the full range of human cognitive abilities.
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Contents
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1 History
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Web Directories, Dictionaries and Encyclopedias
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BotSpot
What's a Bot?
In short: A bot is a software tool for digging through data. You give a bot directions and it bring back answers. The word is short for robot of course, which is derived from the Czech word robota meaning work.
The idea of robots as humanoid machines was first introduced in Karel Capek's 1921 play "R.U.R.," where the playwright conceived Rossum's Universal Robots. Sci-fi writer Isaac Asimov made them famous, beginning with his story I, Robot (1950) and continuing through a string of books known as the Robot Series (see the Isaac Asimov FAQ - for more details including "The Three Laws of Robotics"). - Easily Amused dot com Welcome o' yee of short attention span. Presented here is a collected list of web sites which I found amusing. Although my opinion will vary greatly from yours I hope that you find the majority of these sites at least worth the mouse click to access them.
- Wikipedia A.L.I.C.E. (Artificial Linguistic Internet Computer Entity) is an award-winning natural language processing chatterbot . a program that engages in a conversation with a human by applying some heuristical pattern matching rules to the human's input. It was inspired by Joseph Weizenbaum's classical ELIZA program but takes a quite different approach. It is one of the strongest programs of its type and has won the Loebner Prize three times (in 2000, 2001 and 2004).
- Agentland.com Alice (Artificial Linguistic Internet Computer Entity) is a natural language interface to a telerobot eye. Alice tries ironically to be a computer, so her replies may make some sense but in reality Alice is nothing more than a gigantic pattern-matching case-statement. Remarkably however this elaborate hoax has produced some of the most convincing natural conversations between computer andx humans yet observed.
- Open Directory Chatterbots: ALICE Computers: Artificial Intelligence: Natural Language: Chatterbots: ALICE
- AAAI AI Ethics Any sci-fi buff knows that when computers become self-aware, they ultimately destroy their creators. From 2001: A Space Odyssey to Terminator, the message is clear: The only good self-aware machine is an unplugged one. We may soon find out whether that's true. ... But what about HAL 9000 and the other fictional computers that have run amok?
- American Association for Artificial Intelligence A.I. topics -- Natural LanguageThe value to our society of being able to communicate with computers in everyday "natural" language cannot be overstated. Imagine asking your computer "Does this candidate have a good record on the environment?" or "When is the next televised National League baseball game?" Or being able to tell your PC "Please format my homework the way my English professor likes it".
- American Association for Artificial Intelligence A.I. topics -- The Turing TestAlan Turing proposed an operational test of intelligence as a replacement for the philosophical question, "Can machines think?" Variations of this test have been used to assess performance levels of many AI programs. A restricted adaptation of the Turing Test popularized by the Loebner Competition has been fun, although currently many AI scientists criticize the restricted version of the test because it does not provide insights into the mechanisms of thought.
- www.cs.um.edu.mt/~mros/nlp/ NLP Resource Page
- members.aol.com/lshauser/aiothers.html AI & Other Minds by Larry Hauser.
- www.faqs.org/faqs/ai-faq/general/part6/ Artificial Intelligence FAQ: Open Source AI Software "Chatbots: AI: There is a much maligned chatbot at the Warner Brothers page on the AI movie."
- Sitereview.org A.L.I.C.E is an "Artificial Linguistic Internet Computer Entity" capable of intelligent conversation. She will amaze you with her ability to come up with a relevant response to just about anything! If I didn't know better, I'd think she was human.
- You can become a Botmaster A chat robot is a program that attempts to simulate the conversation or "chat" of a human being. The Chat robot "Eliza" was a well-known early attempt at creating programs that could at least temporarily fool a real human being into thinking they were talking to another person. It is a kind of artificial intelligence.
- Micromegas IA / AI programmes/langages ALICE - Open source natural language artificial intelligence chat robot
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BotSpot
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2 Problems
- 2.1 Deduction, reasoning, problem solving
- 2.2 Knowledge representation
- 2.3 Planning
- 2.4 Learning
- 2.5 Natural language processing
- 2.6 Motion and manipulation
- 2.7 Perception
- 2.8 Social intelligence
- 2.9 Creativity
- 2.10 General intelligence
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3 Approaches
- 3.1 Cybernetics and brain simulation
- 3.2 Symbolic
- 3.3 Sub-symbolic
- 3.4 Statistical
- 3.5 Integrating the approaches
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4 Tools
- 4.1 Search and optimization
- 4.2 Logic
- 4.3 Probabilistic methods for uncertain reasoning
- 4.4 Classifiers and statistical learning methods
- 4.5 Neural networks
- 4.6 Control theory
- 4.7 Languages
- 5 Evaluating progress
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6 Applications
- 6.1 Competitions and prizes
- 6.2 Platforms
- 7 Philosophy
- 8 Prediction
- 9 See also
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10 References
- 10.1 AI textbooks
- 10.2 History of AI
- 10.3 Other sources
- 11 Further reading
- 12 External links
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1 History
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- ~ Bot Industry Survey
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- ~ Foundation Bot Directory
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Form may also refer to:
- Form, a shallow depression or flattened nest of grass used by a hare
- Form (document), a document (printed or electronic) with spaces in which to write or enter data
- Form (education), a class, set or group of students
- Form (exercise), a proper way of performing an exercise
- Form (horse racing), a record of a racehorse's performance, or similarly for an athlete
- Form, a criminal record
- Form, a font designed by Aldo Novarese (1966)
- Form (religion), an academic term for prescriptions or norms on religious practice
- Musical form, a generic type of composition or the structure of a particular piece
- FORM, an American architecture magazine
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Biology:
- Form (botany), a formal taxon at a rank lower than species
- Form (zoology), informal taxa used sometimes in zoology
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Computing:
- Form (web), a document form used on a web page to, typically, submit user data to a server
- Form (programming), a component-based representation of a GUI window
- FORM (symbolic manipulation system), a program for symbolic computations
- Form (computer virus), the most common computer virus of the 1990s
- Oracle Forms, a Rapid Application Development environment for developing database applications
- Windows Forms
- XForms, an XML format for the specification of user interfaces, specifically web forms
- Trapcode Form, a motion graphic editing plug-in from Red Giant Software
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Martial arts:
- Kata (型 or 形), the detailed pattern of defence-and-attack
- Taeguk (Taekwondo) (형), the "forms" used to create a foundation for the teaching of Taekwondo
- Taolu (套路), forms used in Chinese martial arts and sport wushu
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Mathematics:
Algebraic form (homogeneous polynomial), which generalises quadratic forms to degrees 3 and more, also known as quantics or simply forms
Bilinear form, on a vector space V over a field F is a mapping V × V → F that is linear in both arguments
Differential form, a concept from differential topology that combines multi linear forms and smooth functions
Indeterminate form, an algebraic expression that cannot be used to evaluate a limit
Modular form, a (complex) analytic function on the upper half plane satisfying a certain kind of functional equation and growth condition
Multilinear form, which generalises bilinear forms to mappings VN → F
Quadratic form, a homogeneous polynomial of degree two in a number of variables
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Philosophy:
Substantial form
Theory of Forms
Value-form, an approach to understanding the origins of commodity trade and the formation of markets.
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See also
- Formwork, a mould used for concrete construction
- Isoform, several different forms of the same protein
- Sixth form, an English term for the final two years of secondary school
- The Forms (band), an American indie rock band
- Formation (disambiguation)
- Formula (disambiguation)
- Conformity (disambiguation)
- Deformation (disambiguation)
- Inform (disambiguation)
- Reform (disambiguation)
- All pages beginning with "Form"
- All pages with titles containing "Form"
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Form may also refer to:
- Form refers to the shape, visual appearance, or configuration of an object.
- ~ shape
- ~ visual appearance
- ~ configuration
- ~ hare
- ~ Form (document)
- ~ Form (education)
- ~ Form (exercise)
- ~ Form (horse racing)
- ~ criminal record
- ~ Aldo Novarese
- ~ Form (religion)
- ~ Musical form
- ~ FORM
- ~ Form (botany)
- ~ Form (zoology)
- ~ Form (web)
- ~ Form (programming)
- ~ FORM (symbolic manipulation system)
- ~ Form (computer virus)
- ~ Oracle Forms
- ~ Windows Forms
- ~ XForms
- ~ Red Giant Software
- ~ Kata
- ~ Taeguk (Taekwondo)
- ~ Taolu
- ~ homogeneous polynomial
- ~ Bilinear form
- ~ Differential form
- ~ Indeterminate form
- ~ Modular form
- ~ Multilinear form
- ~ Quadratic form
- ~ Substantial form
- ~ Theory of Forms
- ~ Value-form
- ~ edit
- ~ Formwork
- ~ Isoform
- ~ Sixth form
- ~ The Forms (band)
- ~ Formation (disambiguation)
- ~ Formula (disambiguation)
- ~ Conformity (disambiguation)
- ~ Deformation (disambiguation)
- ~ Inform (disambiguation)
- ~ Reform (disambiguation)
- ~ All pages beginning with "Form"
- ~ All pages with titles containing "Form"
- ~ Effect size
- ~ Corrective strategem
- ~ indigo.mm
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