Description

Knowledge representation and reasoning is the foundation of artificial intelligence, declarative programming, and the design of knowledge-intensive software systems capable of performing intelligent tasks. Using logical and probabilistic formalisms based on answer set programming (ASP) and action languages, this book shows how knowledge-intensive systems can be given knowledge about the world and how it can be used to solve non-trivial computational problems. The authors maintain a balance between mathematical analysis and practical design of intelligent agents. All the concepts, such as answering queries, planning, diagnostics, and probabilistic reasoning, are illustrated by programs of ASP. The text can be used for AI-related undergraduate and graduate classes and by researchers who would like to learn more about ASP and knowledge representation.

Knowledge Representation Reasoning and the Design of Intelligent Agents The AnswerSet Programming Approach

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    A Hardback by Michael Gelfond, Yulia Kahl

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      View other formats and editions of Knowledge Representation Reasoning and the Design of Intelligent Agents The AnswerSet Programming Approach by Michael Gelfond

      Publisher: Cambridge University Press
      Publication Date: Publication Date: 3/10/2014 12:00:00 AM
      ISBN13: 9781107029569, 978-1107029569
      ISBN10: 1107029562
      Also in:
      Cognition and cognitive psychology

      Description

      Knowledge representation and reasoning is the foundation of artificial intelligence, declarative programming, and the design of knowledge-intensive software systems capable of performing intelligent tasks. Using logical and probabilistic formalisms based on answer set programming (ASP) and action languages, this book shows how knowledge-intensive systems can be given knowledge about the world and how it can be used to solve non-trivial computational problems. The authors maintain a balance between mathematical analysis and practical design of intelligent agents. All the concepts, such as answering queries, planning, diagnostics, and probabilistic reasoning, are illustrated by programs of ASP. The text can be used for AI-related undergraduate and graduate classes and by researchers who would like to learn more about ASP and knowledge representation.

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