Artificial Intelligence, Second Edition
... Throughout human history, people have used technology to model themselves. There is evidence of this from ancient China, Egypt, and Greece that bears witness to the universality of this activity. Each new technology has, in its turn, been exploited to build intelligent agents or models of mind. Cloc ...
... Throughout human history, people have used technology to model themselves. There is evidence of this from ancient China, Egypt, and Greece that bears witness to the universality of this activity. Each new technology has, in its turn, been exploited to build intelligent agents or models of mind. Cloc ...
Hybrid Reasoning Model for Strengthening the problem solving
... such as the diagnosis of failures in electronic circuits, have a strong scientific basis that supports model based approaches. However, many domains, such as some medical specialties, most design problems, or many financial applications, lack a well-defined scientific theory. Model-based approaches ...
... such as the diagnosis of failures in electronic circuits, have a strong scientific basis that supports model based approaches. However, many domains, such as some medical specialties, most design problems, or many financial applications, lack a well-defined scientific theory. Model-based approaches ...
Task Coordination for Non-cooperative Planning Agents
... tasks. Each agent is assigned a subset of tasks to perform for which it has to construct a plan. Since the agents are non-cooperative, they insist on planning independently and do not want to revise their individual plans when the joint plan has to be assemled from the individual plans. We present a ...
... tasks. Each agent is assigned a subset of tasks to perform for which it has to construct a plan. Since the agents are non-cooperative, they insist on planning independently and do not want to revise their individual plans when the joint plan has to be assemled from the individual plans. We present a ...
Case-Based Reasoning and Expert Systems
... Integrating general expert knowledge in CBR architectures and explicitly considering knowledge evolution A form of learning for generating (more general) knowledge to be executed within a CBR architecture ...
... Integrating general expert knowledge in CBR architectures and explicitly considering knowledge evolution A form of learning for generating (more general) knowledge to be executed within a CBR architecture ...
A Mixed-Initiative Approach to Rule Refinement for Knowledge
... Figure 6: A Mixed-Initiative Integrated Approach to Rule Refinement This significantly reduces the time spent by the expert searching for the steps that need to be refined, and also assures that reasoning steps that need refinement will not be omitted, offering to the expert an interactive framework ...
... Figure 6: A Mixed-Initiative Integrated Approach to Rule Refinement This significantly reduces the time spent by the expert searching for the steps that need to be refined, and also assures that reasoning steps that need refinement will not be omitted, offering to the expert an interactive framework ...
Tabu Search
... considered in the last k best (worst) solutions encourage (or discourage) their selections in future solutions using their frequency of appearance in the set of elite solutions and the quality of solutions which they have appeared in our selection function ...
... considered in the last k best (worst) solutions encourage (or discourage) their selections in future solutions using their frequency of appearance in the set of elite solutions and the quality of solutions which they have appeared in our selection function ...
Proteus: Visual Analogy in Problem Solving
... work is to build a unified theory of visual analogy that not only addresses all major subtasks of analogy, but also uses a uniform knowledge representation for all the subtasks. Also as illustrated by ANALOGY and Letter Spirit, visual analogy refers to analogy based only on the appearance of a situa ...
... work is to build a unified theory of visual analogy that not only addresses all major subtasks of analogy, but also uses a uniform knowledge representation for all the subtasks. Also as illustrated by ANALOGY and Letter Spirit, visual analogy refers to analogy based only on the appearance of a situa ...
Agents - PNU-CS-AI
... Usually, there are several possible actions that can be taken in a given situation. Utility-based agents take action that maximize their reward. ...
... Usually, there are several possible actions that can be taken in a given situation. Utility-based agents take action that maximize their reward. ...
Dynamic Potential-Based Reward Shaping
... can be extended to cover joint action learners. Unlike single-agent reinforcement learning where the goal is to maximise the individual’s reward, when multiple self motivated agents are deployed not all agents can always receive their maximum reward. Instead some compromise must be made, typically t ...
... can be extended to cover joint action learners. Unlike single-agent reinforcement learning where the goal is to maximise the individual’s reward, when multiple self motivated agents are deployed not all agents can always receive their maximum reward. Instead some compromise must be made, typically t ...
Expert System of AI
... and observes a human expert or a group of experts and learns what the experts know, and how they reason with their knowledge. The engineer then translates the knowledge into a computer-usable language, and designs an inference engine, a reasoning structure, that uses the knowledge appropriately. He ...
... and observes a human expert or a group of experts and learns what the experts know, and how they reason with their knowledge. The engineer then translates the knowledge into a computer-usable language, and designs an inference engine, a reasoning structure, that uses the knowledge appropriately. He ...
Matching Conflicts: Functional Validation of Agents
... agent consults its service catalog and returns with several candidate remoteagents and specifies their returning value structures. This is Step 1. outlined above. With this information, the ocean circulation model must validate the functionality of the remote DFTagent, typically written, maintained ...
... agent consults its service catalog and returns with several candidate remoteagents and specifies their returning value structures. This is Step 1. outlined above. With this information, the ocean circulation model must validate the functionality of the remote DFTagent, typically written, maintained ...
3 Experiments
... An institution may also prescribe a pattern of number of individuals needed in each role. In a given organization, roles are filled with agents who occupy roles according to the institutionally prescribed pattern and norms of promotion and demotion we will explore. Agents in an institution must foll ...
... An institution may also prescribe a pattern of number of individuals needed in each role. In a given organization, roles are filled with agents who occupy roles according to the institutionally prescribed pattern and norms of promotion and demotion we will explore. Agents in an institution must foll ...
Role of Expert Systems in Construction Roboticsl
... system separates the program into an explicit knowledge base describing the problem solving strategy and a control program or inference machine which manipulates the knowledge base. The data portion or context describes the problem being solved and the current state of the solution process. Such an ...
... system separates the program into an explicit knowledge base describing the problem solving strategy and a control program or inference machine which manipulates the knowledge base. The data portion or context describes the problem being solved and the current state of the solution process. Such an ...
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 ...
The Comparison between Forward and Backward Chaining
... In the academic field, some students need the best advice in order to improve their situation, and this advice must be provided by the academic management. The academic management should consider many important factors when providing such advise and some of these factors are the mode of study (part- ...
... In the academic field, some students need the best advice in order to improve their situation, and this advice must be provided by the academic management. The academic management should consider many important factors when providing such advise and some of these factors are the mode of study (part- ...
Chapter 8 Multi
... table, then lower your arm’. This would be one of perhaps hundreds of such rules. Whether the condition part of a rule is in fact satisfied at any moment is determined by looking in the agent’s working memory which stores facts such as the location of the arm, the robot’s current goal and its knowle ...
... table, then lower your arm’. This would be one of perhaps hundreds of such rules. Whether the condition part of a rule is in fact satisfied at any moment is determined by looking in the agent’s working memory which stores facts such as the location of the arm, the robot’s current goal and its knowle ...
A Multi-intelligent Agent System for Automatic Construction of Rule
... experts, text documents, and databases based on a multiintelligent agent system. Intelligent agents or software intelligent agents are software entities that run a sequence of action on behalf of a human or another agent independently [8]. A MultiIntelligent Agent (MIA) is a collection of autonomous ...
... experts, text documents, and databases based on a multiintelligent agent system. Intelligent agents or software intelligent agents are software entities that run a sequence of action on behalf of a human or another agent independently [8]. A MultiIntelligent Agent (MIA) is a collection of autonomous ...
Author`s personal copy
... nicely dubbed the ‘‘classic sandwich model’’ by Susan Hurley (1998). Many control architectures are built in this way. Since the 1980s there have been many attempts to challenge this traditional picture particularly in the field of robotics (e.g., Brooks, 1991) but also from a more psychological and ...
... nicely dubbed the ‘‘classic sandwich model’’ by Susan Hurley (1998). Many control architectures are built in this way. Since the 1980s there have been many attempts to challenge this traditional picture particularly in the field of robotics (e.g., Brooks, 1991) but also from a more psychological and ...
Universal Artificial Intelligence: Practical Agents and Fundamental
... A good image of a UAI agent is that of a newborn baby. Knowing nothing about the world, the baby tries different actions and experiences various sensations (percepts) as a consequence. Note that the baby does not initially know about any states of the world—only percepts. Learning is essential for i ...
... A good image of a UAI agent is that of a newborn baby. Knowing nothing about the world, the baby tries different actions and experiences various sensations (percepts) as a consequence. Note that the baby does not initially know about any states of the world—only percepts. Learning is essential for i ...
View - Association for Computational Creativity
... Agent 1 uses an intermediate propositional knowledge representation for working memory. In the agent’s representation, each frame in an RPM consists of objects, and each object consists of the following attributes: shape, size, fill, rotation, and relative-position to other shapes. A library ...
... Agent 1 uses an intermediate propositional knowledge representation for working memory. In the agent’s representation, each frame in an RPM consists of objects, and each object consists of the following attributes: shape, size, fill, rotation, and relative-position to other shapes. A library ...
From Agent Theory to Agent Construction: A Case Study
... an implemented system and then formalizing the semantics in an agent language which can be viewed as an abstraction of the implemented system, and which allows agent programs to be written and interpreted [26]. Goodwin has also attempted to bridge the gap by providing a formal description in the for ...
... an implemented system and then formalizing the semantics in an agent language which can be viewed as an abstraction of the implemented system, and which allows agent programs to be written and interpreted [26]. Goodwin has also attempted to bridge the gap by providing a formal description in the for ...
AAAI Proceedings Template
... Agent 1 uses an intermediate propositional knowledge representation for working memory. In the agent’s representation, each frame in an RPM consists of objects, and each object consists of the following attributes: shape, size, fill, rotation, and relative-position to other shapes. A library of shap ...
... Agent 1 uses an intermediate propositional knowledge representation for working memory. In the agent’s representation, each frame in an RPM consists of objects, and each object consists of the following attributes: shape, size, fill, rotation, and relative-position to other shapes. A library of shap ...
A Normal Form for Classical Planning Tasks
... The design and study of classical planning techniques such as heuristics or search algorithms is often considerably simpler when focusing on planning tasks with a restricted structure. Two assumptions that are frequently useful are that operators only change variables for which they have a defined p ...
... The design and study of classical planning techniques such as heuristics or search algorithms is often considerably simpler when focusing on planning tasks with a restricted structure. Two assumptions that are frequently useful are that operators only change variables for which they have a defined p ...
Reinforcement Learning and Automated Planning
... Usually, in the description of domains, action schemas (also called operators) are used instead of actions. Action schemas contain variables that can be instantiated using the available objects and this makes the encoding of the domain easier. The choice of the language in which the planning problem ...
... Usually, in the description of domains, action schemas (also called operators) are used instead of actions. Action schemas contain variables that can be instantiated using the available objects and this makes the encoding of the domain easier. The choice of the language in which the planning problem ...
Generation of Macro-operators via Investigation of Actions
... a set of predicates that are true in s. Action a is a 3-tuple (p(a), e− (a), e+ (a)) of sets of predicates such that p(a) is a set of predicates representing the precondition of action a, e− (a) is a set of negative effects of action a, e+ (a) is a set of positive effects of action a, and e− (a) ∩ e ...
... a set of predicates that are true in s. Action a is a 3-tuple (p(a), e− (a), e+ (a)) of sets of predicates such that p(a) is a set of predicates representing the precondition of action a, e− (a) is a set of negative effects of action a, e+ (a) is a set of positive effects of action a, and e− (a) ∩ e ...
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.