CIS 690 (Implementation of High
... • Other (rule-based, fuzzy, neural, genetic) – Search – Machine learning – Planning ...
... • Other (rule-based, fuzzy, neural, genetic) – Search – Machine learning – Planning ...
A Foundational Architecture for Artificial General Intelligence
... importance, urgency, and insistence. Procedural memory then uses the contents of consciousness, what comes to attention, to recruit only those actions that might be possible and useful in the current situation, yet another filtering process. Our final filtering process is action selection, the proce ...
... importance, urgency, and insistence. Procedural memory then uses the contents of consciousness, what comes to attention, to recruit only those actions that might be possible and useful in the current situation, yet another filtering process. Our final filtering process is action selection, the proce ...
Belief-optimal Reasoning for Cyber
... Heuristic Search Hypothesis (Newell and Simon, 1976) “The solutions to problems are represented as symbol structures. A physical symbol system exercises its intelligence in problem solving by search - that is, by generating and progressively modifying symbol structures until it produces a solution ...
... Heuristic Search Hypothesis (Newell and Simon, 1976) “The solutions to problems are represented as symbol structures. A physical symbol system exercises its intelligence in problem solving by search - that is, by generating and progressively modifying symbol structures until it produces a solution ...
A Methodology for Modeling and Representing Expert Knowledge
... agent is built, from being programmed by a knowledge engineer (based on what he or she has learned from a domain expert) to being directly taught by a domain expert that receives limited or no support from a knowledge engineer. The investigated approach, called Disciple (Tecuci, 1998; Tecuci et al., ...
... agent is built, from being programmed by a knowledge engineer (based on what he or she has learned from a domain expert) to being directly taught by a domain expert that receives limited or no support from a knowledge engineer. The investigated approach, called Disciple (Tecuci, 1998; Tecuci et al., ...
A Model for Design of Societies of Cooperative Agents
... agents might have. A list of common agent attributes is shown below [BRA 97]. • Adaptivity: the ability to learn and improve with experience. • Autonomy: goal-directness, proactive and self-starting behaviour. • Collaborative behaviour: the ability to work with other agents to achieve a common goal. ...
... agents might have. A list of common agent attributes is shown below [BRA 97]. • Adaptivity: the ability to learn and improve with experience. • Autonomy: goal-directness, proactive and self-starting behaviour. • Collaborative behaviour: the ability to work with other agents to achieve a common goal. ...
The Non-Action-Centered
... connects to its corresponding (micro)features (distributed representation) in the bottom level ...
... connects to its corresponding (micro)features (distributed representation) in the bottom level ...
Agents-part1 - Dr Shahriar Bijani
... Distributed rational decision making extensively studied in economics, game theory very popular Many strengths but also objections ...
... Distributed rational decision making extensively studied in economics, game theory very popular Many strengths but also objections ...
Introduction of Artificial Moral Agent Incorporating Soar and Global
... intelligent reasoning of humanoid robot. Dynamic Encoding Algorithm for Searches (DEAS) ...
... intelligent reasoning of humanoid robot. Dynamic Encoding Algorithm for Searches (DEAS) ...
Lecture slides - Computer Science
... Huge amounts of info, of varying relevance. Hence: search, satisficing, graceful degradation, heuristics. Context-sensitivity; incl. relativity to agents’ purposes (e.g., in vision and language interpretation). Task variability, learning, adaptation, repair (e.g., of plans). ...
... Huge amounts of info, of varying relevance. Hence: search, satisficing, graceful degradation, heuristics. Context-sensitivity; incl. relativity to agents’ purposes (e.g., in vision and language interpretation). Task variability, learning, adaptation, repair (e.g., of plans). ...
Improving Construction and Maintenance of Agent-based
... knowledge. However, a shell is limited in terms of extending its functionality, it works as a black-box,the interface is very limited and the developer has little or no power to enhance an algorithm within the shell, the developer needs to use the pre-defined interfaces, if there are features to be ...
... knowledge. However, a shell is limited in terms of extending its functionality, it works as a black-box,the interface is very limited and the developer has little or no power to enhance an algorithm within the shell, the developer needs to use the pre-defined interfaces, if there are features to be ...
On Efficiency of Learning: A Framework and Justification.
... design of improved learning (algorithm). The body of this knowledge is vast. What parts should be used? My approach is to use all meta-knowledge that can be integrated into an efficient learning system. It is also the solution of the efficiency of learning: Each piece of this meta-knowledge should s ...
... design of improved learning (algorithm). The body of this knowledge is vast. What parts should be used? My approach is to use all meta-knowledge that can be integrated into an efficient learning system. It is also the solution of the efficiency of learning: Each piece of this meta-knowledge should s ...
MS PowerPoint format - Kansas State University
... – Able to reason over goal, intermediate, and initial states – Basis: automated reasoning • One implementation: theorem proving (first-order logic) • Powerful representation language and inference mechanism ...
... – Able to reason over goal, intermediate, and initial states – Basis: automated reasoning • One implementation: theorem proving (first-order logic) • Powerful representation language and inference mechanism ...
1. Procedural knowledge Vs Declarative Knowledge - E
... only if the facts are not available) there are no facts with predicate pet. But there are two rules rather than one, which contain the predicate on the right hand side. So one of them must be selected. The selection is based on the order in which they are given. The first one fails, because there is ...
... only if the facts are not available) there are no facts with predicate pet. But there are two rules rather than one, which contain the predicate on the right hand side. So one of them must be selected. The selection is based on the order in which they are given. The first one fails, because there is ...
AAAI Proceedings Template - Department of Communication and
... and links does not appear to be the most effective representation from which to make geometric inferences. In many important Cognitive Architectures (e.g. SOAR, ACT-R, Clarion), symbolic representations are used (Langley 2009). While symbolic-like representations are, in our view (Franklin, 1995) ne ...
... and links does not appear to be the most effective representation from which to make geometric inferences. In many important Cognitive Architectures (e.g. SOAR, ACT-R, Clarion), symbolic representations are used (Langley 2009). While symbolic-like representations are, in our view (Franklin, 1995) ne ...
Four approaches to defining AI systems Cognitive science Rational
... sequence of actions that will achieve a goal state ...
... sequence of actions that will achieve a goal state ...
Test-1 Solution Thinking humanly Thinking rationally Acting
... The time complexity of a depth-first Search to depth d is O(b^d) since it generates the same set of nodes as breadth-first search, but simply in a different order. Thus practically depth-first search is time-limited rather than space-limited. ...
... The time complexity of a depth-first Search to depth d is O(b^d) since it generates the same set of nodes as breadth-first search, but simply in a different order. Thus practically depth-first search is time-limited rather than space-limited. ...
Intelligent DSS - Telkom University
... • Types of tools for developing an expert system (contd) – Rule set builder: (software for building, maintaining, and compiling rule sets) • Building: specifying rules and specifying knowledge about usage • Maintenance: changing specifications as new reasoning expertise becomes ...
... • Types of tools for developing an expert system (contd) – Rule set builder: (software for building, maintaining, and compiling rule sets) • Building: specifying rules and specifying knowledge about usage • Maintenance: changing specifications as new reasoning expertise becomes ...
RTF - University of Michigan
... than a priori knowledge. 1 This capability is difficult to achieve because descriptions written by different developers may be terminologically heterogenous—including vocabulary from ontologies that are potentially inconsistent. For example, one agent might describe its service as (a formal equivale ...
... than a priori knowledge. 1 This capability is difficult to achieve because descriptions written by different developers may be terminologically heterogenous—including vocabulary from ontologies that are potentially inconsistent. For example, one agent might describe its service as (a formal equivale ...
OpenCogPrime - Ben Goertzel
... real inputs, but not yet internal variables or higher order functions) A version of ECAN, which is restricted to the detection and use of binary attentional patterns between Atoms; and also, a simple forgetting mechanism that removes Atoms with low long-term ...
... real inputs, but not yet internal variables or higher order functions) A version of ECAN, which is restricted to the detection and use of binary attentional patterns between Atoms; and also, a simple forgetting mechanism that removes Atoms with low long-term ...
A Unified Cognitive Architecture for Physical Agents
... makes it the focus of cognitive attention, even if this means dropping a goal that was being pursued on the previous cycle. If all goals are satisfied, then the system has no focus on that cycle, although this may change later, leading the agent to refocus on goals that it achieved previously. I CAR ...
... makes it the focus of cognitive attention, even if this means dropping a goal that was being pursued on the previous cycle. If all goals are satisfied, then the system has no focus on that cycle, although this may change later, leading the agent to refocus on goals that it achieved previously. I CAR ...
MLECOG - Motivated Learning Embodied Cognitive Architecture
... motivations to manage goals and stimulate the agent’s behavior. The mental saccade mechanism is simpler than the coalition of cognitive processes used in LIDA, since it establishes a cognitive process only after the focus of attention is shifted to the selected part of associative memory. Similar to ...
... motivations to manage goals and stimulate the agent’s behavior. The mental saccade mechanism is simpler than the coalition of cognitive processes used in LIDA, since it establishes a cognitive process only after the focus of attention is shifted to the selected part of associative memory. Similar to ...
An Ontology-Based Symbol Grounding System for Human
... This paper has discussed perceptual anchoring and its potential to enable HRI via symbolic representations of objects. The work presented here is a first step towards enabling perceptual anchoring to operate with larger symbolic (semantic) models such as ontologies, with a focus on large scale and l ...
... This paper has discussed perceptual anchoring and its potential to enable HRI via symbolic representations of objects. The work presented here is a first step towards enabling perceptual anchoring to operate with larger symbolic (semantic) models such as ontologies, with a focus on large scale and l ...
Agent and Environment - Computer Science and Engineering
... AI: study of rational agents A rational agent carries out an action with the best outcome after considering past and current percepts A rational agent should act so as to maximize performance, given knowledge of the environment ...
... AI: study of rational agents A rational agent carries out an action with the best outcome after considering past and current percepts A rational agent should act so as to maximize performance, given knowledge of the environment ...
記錄 編號 6668 狀態 NC094FJU00392004 助教 查核 索書 號 學校
... intelligent agent. When agents are initially created, they have some goals and few capabilities. Each capability composes by one or more actions. These capabilities can perform some actions to satisfy their goals. They strive to adapt themselves to the low capabilities. Reinforcement learning method ...
... intelligent agent. When agents are initially created, they have some goals and few capabilities. Each capability composes by one or more actions. These capabilities can perform some actions to satisfy their goals. They strive to adapt themselves to the low capabilities. Reinforcement learning method ...
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.