PDF only
... Those hypotheses are then refined by gathering addi tional evidence, when available, that might confirm or refute hypotheses lower in the hierarchy. In this way, the process tries to establish the most specific solution possible. In very simple situations, hierarchical classifica tion is the only ...
... Those hypotheses are then refined by gathering addi tional evidence, when available, that might confirm or refute hypotheses lower in the hierarchy. In this way, the process tries to establish the most specific solution possible. In very simple situations, hierarchical classifica tion is the only ...
Learning Planning Operators by Observation and Practice
... Figure 4: The secondobservation of the operator GOTO-DR The systeminitializes the ISGby setting its root to the virtual operator *finish*. The last operator in the episode must be achieving sometop-level goals. Since everything Refining Operators with Practice Because of the incorin the delta-state ...
... Figure 4: The secondobservation of the operator GOTO-DR The systeminitializes the ISGby setting its root to the virtual operator *finish*. The last operator in the episode must be achieving sometop-level goals. Since everything Refining Operators with Practice Because of the incorin the delta-state ...
Expert Systems - Department of Computer Science
... If this intuition is correct, there is more to real expert understanding than following rules. BUT a few problems where (rule driven) expert systems can perform as well as experts. And even in the absence of claims that expert systems think like humans, these may well be a useful tools. Probably wo ...
... If this intuition is correct, there is more to real expert understanding than following rules. BUT a few problems where (rule driven) expert systems can perform as well as experts. And even in the absence of claims that expert systems think like humans, these may well be a useful tools. Probably wo ...
Planning with Different Forms of Domain
... a planner is to identify the classes of knowledge to incorporate and to devise a means of representing and reasoning with this knowledge. In the past, planners such as TLPlan and TALplan have exploited domain-dependent temporal knowledge; SHOP and various hierarchical task network (HTN) planners hav ...
... a planner is to identify the classes of knowledge to incorporate and to devise a means of representing and reasoning with this knowledge. In the past, planners such as TLPlan and TALplan have exploited domain-dependent temporal knowledge; SHOP and various hierarchical task network (HTN) planners hav ...
knowledge base
... developed by a human expert. The second example involves expert system rules derived automatically by an inductive machine-learning algorithm based on training data that is input by humans into the system. Both methods are used to identify white fir forest stands on Maple Mountain in Utah County, Ut ...
... developed by a human expert. The second example involves expert system rules derived automatically by an inductive machine-learning algorithm based on training data that is input by humans into the system. Both methods are used to identify white fir forest stands on Maple Mountain in Utah County, Ut ...
View PDF - CiteSeerX
... chitecture for a higher level of parallelism will be intro duced. This increasing availability of high performance computers, from personal computers to massively par allel supercomputers, will allow experiments on simu lated massive parallelism to be made at numerous places. Thus, computational ...
... chitecture for a higher level of parallelism will be intro duced. This increasing availability of high performance computers, from personal computers to massively par allel supercomputers, will allow experiments on simu lated massive parallelism to be made at numerous places. Thus, computational ...
Multi-Agent Case-Based Diagnosis in the Aircraft Domain
... weather conditions, temperature, etc.), and logbook entries can be received, too. The PFR data and the additional data have to be correlated to assign the additional data to the corresponding PFR item. This task is done by the correlation agent. The extended PFR items are sent to the coordination ag ...
... weather conditions, temperature, etc.), and logbook entries can be received, too. The PFR data and the additional data have to be correlated to assign the additional data to the corresponding PFR item. This task is done by the correlation agent. The extended PFR items are sent to the coordination ag ...
hierarchical intelligent simulation
... knowledge, representing principles of approach that are structured by even higher levels, containing hierarchical type theories. A possible interpretation of such hierarchies is: real time of the bottom levels - corresponding to primary knowledge/ behavior/ methods, is managed at upper levels - corr ...
... knowledge, representing principles of approach that are structured by even higher levels, containing hierarchical type theories. A possible interpretation of such hierarchies is: real time of the bottom levels - corresponding to primary knowledge/ behavior/ methods, is managed at upper levels - corr ...
Flexible and Scalable Query Planning in Mediators
... These three aspects of mediator systems, namely, the need for traditional query optimization, the distributed environment, and the semantic heterogeneity, are also the sources of complexity that result in the highly combinatorial nature query planning in mediators. Instead of exhaustively searching ...
... These three aspects of mediator systems, namely, the need for traditional query optimization, the distributed environment, and the semantic heterogeneity, are also the sources of complexity that result in the highly combinatorial nature query planning in mediators. Instead of exhaustively searching ...
Lecture I -- Introduction and Intelligent Agent
... Abstractly, an agent is a function from percept histories to actions: ...
... Abstractly, an agent is a function from percept histories to actions: ...
Lecture I -- Introduction and Intelligent Agent
... Abstractly, an agent is a function from percept histories to actions: ...
... Abstractly, an agent is a function from percept histories to actions: ...
Multi-Agent System
... • A multi-agent system (MAS) is a system composed of multiple interacting intelligent agents. • Multi-agent systems can be used to solve problems which are difficult or impossible for an individual agent or monolithic system to solve. • Examples of problems which are appropriate to multi-agent syste ...
... • A multi-agent system (MAS) is a system composed of multiple interacting intelligent agents. • Multi-agent systems can be used to solve problems which are difficult or impossible for an individual agent or monolithic system to solve. • Examples of problems which are appropriate to multi-agent syste ...
A concise review on multi-agent teams: contributions and
... complex examples where humans are modeled as agents. While some of the human properties may not make sense in an agent context, some do. For instance, the dynamics of competences through learning and experience and the cultural values could be used to program more sophisticated agents, specially whe ...
... complex examples where humans are modeled as agents. While some of the human properties may not make sense in an agent context, some do. For instance, the dynamics of competences through learning and experience and the cultural values could be used to program more sophisticated agents, specially whe ...
Chapter 1: Introduction to Expert Systems
... • Programmer does not specify how to achieve a goal at the algorithm level. • Induction-based programming – the program learns by generalizing from a sample. ...
... • Programmer does not specify how to achieve a goal at the algorithm level. • Induction-based programming – the program learns by generalizing from a sample. ...
Chapter 1: Introduction to Expert Systems
... • Programmer does not specify how to achieve a goal at the algorithm level. • Induction-based programming – the program learns by generalizing from a sample. ...
... • Programmer does not specify how to achieve a goal at the algorithm level. • Induction-based programming – the program learns by generalizing from a sample. ...
intelligent agent
... Agent Definition (1) • An agent is an entity which is: – Situated in some environment. – Autonomous, in the sense that it can act without direct intervention from humans or other software processes, and controls over its own actions and internal state. – Flexible which means: • Responsive (reactive ...
... Agent Definition (1) • An agent is an entity which is: – Situated in some environment. – Autonomous, in the sense that it can act without direct intervention from humans or other software processes, and controls over its own actions and internal state. – Flexible which means: • Responsive (reactive ...
Artificial Intelligence and Expert Systems
... Apply knowledge to manipulate the environment Thinking and reasoning Recognizing and judging the relative importance of different elements in a situation ...
... Apply knowledge to manipulate the environment Thinking and reasoning Recognizing and judging the relative importance of different elements in a situation ...
Managing the Digital Firm - Department of Computer Engineering
... The knowledge typically comes from a series of conversations between the developer of the expert system and one or more experts. The completed system applies the knowledge to problems specified by a user. ...
... The knowledge typically comes from a series of conversations between the developer of the expert system and one or more experts. The completed system applies the knowledge to problems specified by a user. ...
Using General-Purpose Planning for Action Selection in
... a domain-independent planner which manages the interactions with customers, tracks multiple drink orders, and gathers additional information as needed with follow-up questions (Petrick and Foster 2013). In particular, the task of interacting with human customers is mixed with the physical task of en ...
... a domain-independent planner which manages the interactions with customers, tracks multiple drink orders, and gathers additional information as needed with follow-up questions (Petrick and Foster 2013). In particular, the task of interacting with human customers is mixed with the physical task of en ...
Managing the Digital Firm
... The knowledge typically comes from a series of conversations between the developer of the expert system and one or more experts. The completed system applies the knowledge to problems specified by a user. ...
... The knowledge typically comes from a series of conversations between the developer of the expert system and one or more experts. The completed system applies the knowledge to problems specified by a user. ...
What kind of cognitive process is argumentation?
... – Knowledge acquisition system (not necessarily perceptual, but necessarily verbal) • Language of argumentation can be simplified or purely formal in minimal agents but shouldn't be too simple – Knowledge representation system – Argumentation module, implementing a formal model of verbal reasoning a ...
... – Knowledge acquisition system (not necessarily perceptual, but necessarily verbal) • Language of argumentation can be simplified or purely formal in minimal agents but shouldn't be too simple – Knowledge representation system – Argumentation module, implementing a formal model of verbal reasoning a ...
An Integrated Approach of Learning, Planning, and Execution
... For LOPE, as for many other systems, there is a difference between the world states, common to classical planning, and the observations it perceives. While classical planners are mainly interested in the high-level descriptions of the states (e.g., on (A,B) in the blocksworld), LOPE builds its opera ...
... For LOPE, as for many other systems, there is a difference between the world states, common to classical planning, and the observations it perceives. While classical planners are mainly interested in the high-level descriptions of the states (e.g., on (A,B) in the blocksworld), LOPE builds its opera ...
marked
... Mapping p: percept sequence action Representing p as list of pairs: infinite (unless explicitly bounded) Using p: ideal mapping from percepts to actions (i.e., ideal agent) Finding explicit p: in principle, could use trial and error Other (implicit) representations may be easier to acqui ...
... Mapping p: percept sequence action Representing p as list of pairs: infinite (unless explicitly bounded) Using p: ideal mapping from percepts to actions (i.e., ideal agent) Finding explicit p: in principle, could use trial and error Other (implicit) representations may be easier to acqui ...
cs-171-01-Agents_smrq16
... world? • Single agent (vs. multi-agent): An agent operating by itself in an environment. Does the other agent interfere with my performance measure? ...
... world? • Single agent (vs. multi-agent): An agent operating by itself in an environment. Does the other agent interfere with my performance measure? ...
cs-171-01-Agents
... world? • Single agent (vs. multi-agent): An agent operating by itself in an environment. Does the other agent interfere with my performance measure? ...
... world? • Single agent (vs. multi-agent): An agent operating by itself in an environment. Does the other agent interfere with my performance measure? ...
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.