Influence-based Abstraction for Multiagent Systems
... POSGs can be decomposed into local models. We formalize the interface between such local models as the influence agents can exert on one another; and we prove that this interface is sufficient for decoupling them. The resulting influence-based abstraction substantially generalizes previous work on e ...
... POSGs can be decomposed into local models. We formalize the interface between such local models as the influence agents can exert on one another; and we prove that this interface is sufficient for decoupling them. The resulting influence-based abstraction substantially generalizes previous work on e ...
Belief Revision in Multi-Agent Systems
... design and implementation of a Distributed Assumption based Truth Maintenance System (DATMS) appropriate for controlling cooperative problem solving in a dynamic real world multi-agent community. Our DATMS works on the principle of local coherence which means that different agents can have different ...
... design and implementation of a Distributed Assumption based Truth Maintenance System (DATMS) appropriate for controlling cooperative problem solving in a dynamic real world multi-agent community. Our DATMS works on the principle of local coherence which means that different agents can have different ...
Applying Global Workspace Theory to the Frame Problem
... inference, they too are undecidable, regardless of the problem size. Therefore the real concern over computational feasibility is not an accompaniment to the presumption that first-order logical inference is taking place. 13 The real worry, in the context of the frame problem, seems to be that the s ...
... inference, they too are undecidable, regardless of the problem size. Therefore the real concern over computational feasibility is not an accompaniment to the presumption that first-order logical inference is taking place. 13 The real worry, in the context of the frame problem, seems to be that the s ...
CMSC 372 Artificial Intelligence
... state, the agent’s current conception of the world state model, a description of how the next state depends on current state and action rules, a set of condition-action rules action, the most recent action, initially none ...
... state, the agent’s current conception of the world state model, a description of how the next state depends on current state and action rules, a set of condition-action rules action, the most recent action, initially none ...
CS 561a: Introduction to Artificial Intelligence
... • Manage the explosive growth of information. • Manipulate or collate information from many distributed sources. • Information agents can be mobile or static. ...
... • Manage the explosive growth of information. • Manipulate or collate information from many distributed sources. • Information agents can be mobile or static. ...
How Can Expertise be Defined?
... social policy governing exposure and safety standards. If the “experts” are experts, why do they disagree? And since they do disagree, how can one rely on their judgments in setting policy? The challenge to cognitive psychology is to generate an operational definition of expertise, one that focuses ...
... social policy governing exposure and safety standards. If the “experts” are experts, why do they disagree? And since they do disagree, how can one rely on their judgments in setting policy? The challenge to cognitive psychology is to generate an operational definition of expertise, one that focuses ...
Artificial Cognitive Systems
... “Cognitive Architectures: Where do we go from here?”, Proc. Conf. Artificial General Intelligence, 122-136, 2008. (17 cognitive architectures) D. Vernon, G. Metta, and G. Sandini, "A Survey of Artificial Cognitive Systems: Implications for the Autonomous Development of Mental Capabilities in Computa ...
... “Cognitive Architectures: Where do we go from here?”, Proc. Conf. Artificial General Intelligence, 122-136, 2008. (17 cognitive architectures) D. Vernon, G. Metta, and G. Sandini, "A Survey of Artificial Cognitive Systems: Implications for the Autonomous Development of Mental Capabilities in Computa ...
Goal-Based Action Priors - Humans to Robots Laboratory
... Goal-based action priors build on Object-Oriented MDPs (OO-MDPs) (Diuk, Cohen, and Littman 2008). An OOMDP efficiently represents the state of an MDP through the use of objects and predicates. An OO-MDP state is a collection of objects, O = {o1 , . . . , oo }. Each object oi belongs to a class, cj ∈ ...
... Goal-based action priors build on Object-Oriented MDPs (OO-MDPs) (Diuk, Cohen, and Littman 2008). An OOMDP efficiently represents the state of an MDP through the use of objects and predicates. An OO-MDP state is a collection of objects, O = {o1 , . . . , oo }. Each object oi belongs to a class, cj ∈ ...
CS 561a: Introduction to Artificial Intelligence
... should eventually succeed. It is a race, but both racers seem to be walking. [John McCarthy] CS 561, Lecture 1 ...
... should eventually succeed. It is a race, but both racers seem to be walking. [John McCarthy] CS 561, Lecture 1 ...
An Integrated Toolkit for Modern Action Planning - PuK
... path scheduling (PERT) such a plan can be computed in optimal time [6]. The approach extends to timed initial literals and action execution time windows. Operator dependency induces a partial ordering in a sequence of actions. In order to derive posterior schedules of sequential plans in temporal pl ...
... path scheduling (PERT) such a plan can be computed in optimal time [6]. The approach extends to timed initial literals and action execution time windows. Operator dependency induces a partial ordering in a sequence of actions. In order to derive posterior schedules of sequential plans in temporal pl ...
The role of Artificial Intelligence in Knowledge Management
... industrial expert systems team for more than a decade, the primary guest editor’s observation is that the emphasis on developing fully-fledged AI (or expert) systems has very much shifted. Due to advances in Web-based technology and component-based development, there are, in fact, plenty of opportun ...
... industrial expert systems team for more than a decade, the primary guest editor’s observation is that the emphasis on developing fully-fledged AI (or expert) systems has very much shifted. Due to advances in Web-based technology and component-based development, there are, in fact, plenty of opportun ...
To Developed Tool, an Intelligent Agent for AutomaticKnowledge
... The term expert system tools describes the software system that is used for constructing an expert system [3], most expert systems are developed using specialized software tools called shells. These shells provided with an inference mechanism such as backward chaining, forward chaining or both, and ...
... The term expert system tools describes the software system that is used for constructing an expert system [3], most expert systems are developed using specialized software tools called shells. These shells provided with an inference mechanism such as backward chaining, forward chaining or both, and ...
Intelligent Virtual Environments - A State-of-the
... required to develop basic control architectures – often adapted directly from robotics – it becomes possible with intelligent virtual agents, or synthetic characters, to investigate the modelling of emotion and the basis for agent social behaviour. This work can be carried out at both the behavioura ...
... required to develop basic control architectures – often adapted directly from robotics – it becomes possible with intelligent virtual agents, or synthetic characters, to investigate the modelling of emotion and the basis for agent social behaviour. This work can be carried out at both the behavioura ...
Temporal Symbolic Integration Applied to a Multimodal System
... core component consists of an inference engine, that matches preconditions of a ruleset against the knowledge that is currently present in memory and executes the consequences (the rule ”fires”). The rule in our example will fire if two symbols for “pointing handshape” and “far away from body” are p ...
... core component consists of an inference engine, that matches preconditions of a ruleset against the knowledge that is currently present in memory and executes the consequences (the rule ”fires”). The rule in our example will fire if two symbols for “pointing handshape” and “far away from body” are p ...
study of difference between forward and backward reasoning
... resulting in the addition of new information to its dataset. In other words, it starts with some facts and applies rules to find all possible conclusions. Therefore, it is also known as Data Driven Approach [1]. ...
... resulting in the addition of new information to its dataset. In other words, it starts with some facts and applies rules to find all possible conclusions. Therefore, it is also known as Data Driven Approach [1]. ...
Learning to Plan in Complex Stochastic Domains
... grow exponentially with respect to the number of objects in the environment. For instance, when a robot is manipulating objects, an object can be placed anywhere in a large set of locations. The size of the state space explodes exponentially with the number of objects and locations, which limits the ...
... grow exponentially with respect to the number of objects in the environment. For instance, when a robot is manipulating objects, an object can be placed anywhere in a large set of locations. The size of the state space explodes exponentially with the number of objects and locations, which limits the ...
AI Robotics - Kutztown University
... Cognitive functions that enable people to deal effectively with spatial relations, visual spatial tasks and orientation of objects in space. One aspect of these cognitive skills is spatial orientation, which is the ability to orient oneself in space relative to objects and events; and the awaren ...
... Cognitive functions that enable people to deal effectively with spatial relations, visual spatial tasks and orientation of objects in space. One aspect of these cognitive skills is spatial orientation, which is the ability to orient oneself in space relative to objects and events; and the awaren ...
ADVANCES IN KNOWLEDGE ACQUISITION AND
... The field of knowledge acquisition has been heavily studied from initial automated machine learning approaches (e.g., perceptrons20), to semi-automated knowledge engineering2, to more robust automated approaches (e.g., neural networks21, symbolic rule learning18), and most recently to proven, practi ...
... The field of knowledge acquisition has been heavily studied from initial automated machine learning approaches (e.g., perceptrons20), to semi-automated knowledge engineering2, to more robust automated approaches (e.g., neural networks21, symbolic rule learning18), and most recently to proven, practi ...
Reconstructing Physical Symbol Systems
... Where we part company with Vera and Simon is the application of chunking to non-symbolic domains, such as motor skills. Why assume that bicycle riding, for example, is a symbol processing task? We see nothing in the structure of bicycle riding that requires arbitrary designation ability or combinato ...
... Where we part company with Vera and Simon is the application of chunking to non-symbolic domains, such as motor skills. Why assume that bicycle riding, for example, is a symbol processing task? We see nothing in the structure of bicycle riding that requires arbitrary designation ability or combinato ...
What Is an Intelligent Agent?
... "Firstly, agents may be classified by their mobility, i.e. by their ability to move around some network. This yields the classes of static or mobile agents. Secondly, they may be classed as either deliberative or reactive. Deliberative agents derive from the deliberative thinking paradigm: the agent ...
... "Firstly, agents may be classified by their mobility, i.e. by their ability to move around some network. This yields the classes of static or mobile agents. Secondly, they may be classed as either deliberative or reactive. Deliberative agents derive from the deliberative thinking paradigm: the agent ...
Strong Cyclic Planning with Incomplete Information and Sensing
... the logic ALCKN F (see (De Giacomo et al. 1997; Iocchi et al. 2000) for details). More specifically, we introduce a set of primitive properties (or fluents) P , that will be used to characterize the possible states of the world. The primitive fluents P may either be either predicates or terms contai ...
... the logic ALCKN F (see (De Giacomo et al. 1997; Iocchi et al. 2000) for details). More specifically, we introduce a set of primitive properties (or fluents) P , that will be used to characterize the possible states of the world. The primitive fluents P may either be either predicates or terms contai ...
CUUS366-02 clean wjc
... complex adaptive systems (Holland, 1996), and so on. These are modeling approaches with a broadly shared perspective on how causality operates in many natural systems and in some designed systems (Altman & Rogoff, 1987). For example, systems thinking views human expertise as occurring within and dev ...
... complex adaptive systems (Holland, 1996), and so on. These are modeling approaches with a broadly shared perspective on how causality operates in many natural systems and in some designed systems (Altman & Rogoff, 1987). For example, systems thinking views human expertise as occurring within and dev ...
Chapter 1 The Architecture of Human
... of intelligent unmanned automated vehicles, is a crisp embodiment of many ideas emergent from the field of intelligent control systems. • Deep learning networks as a model of perception (and action and reinforcement learning), as embodied for example in the work of Itamar Arel? and Jeff Hawkins.? Th ...
... of intelligent unmanned automated vehicles, is a crisp embodiment of many ideas emergent from the field of intelligent control systems. • Deep learning networks as a model of perception (and action and reinforcement learning), as embodied for example in the work of Itamar Arel? and Jeff Hawkins.? Th ...
Emotions — The missing link? Rodrigo Ventura
... On the other hand, the cognitive processing mechanism aims at finding a pattern (or a set of patterns) that approximately match the incoming image — the one under processing. Due to the search which is presupposed in such a process, it is forcibly time consuming. To circumvent this problem, cognitiv ...
... On the other hand, the cognitive processing mechanism aims at finding a pattern (or a set of patterns) that approximately match the incoming image — the one under processing. Due to the search which is presupposed in such a process, it is forcibly time consuming. To circumvent this problem, cognitiv ...
Unit 4_Expert Systems and AI
... Of course, the term intelligence covers many cognitive skills, including the ability to solve problems, learn, and understand language; AI addresses all of those. But most progress to date in AI has been made in the area of problem solving -- concepts and methods for building programs that reason ab ...
... Of course, the term intelligence covers many cognitive skills, including the ability to solve problems, learn, and understand language; AI addresses all of those. But most progress to date in AI has been made in the area of problem solving -- concepts and methods for building programs that reason ab ...
Soar (cognitive architecture)
Soar is a cognitive architecture, created by John Laird, Allen Newell, and Paul Rosenbloom at Carnegie Mellon University, now maintained by John Laird's research group at the University of Michigan. It is both a view of what cognition is and an implementation of that view through a computer programming architecture for artificial intelligence (AI). Since its beginnings in 1983 and its presentation in a paper in 1987, it has been widely used by AI researchers to model different aspects of human behavior.