An Overview of Knowledge Management and Knowledge Representation





Knowledge Representation, Reasoning and Declarative Problem Solving, 1st Edition, 2003, Chitta Baral

  • Readership: graduates, researchers, software pactitioners, knowledge engineers
  • Chitta Baral demonstrates how to write programs that behave intelligently by giving them the ability to express knowledge and reason about it. He presents a language, AnsProlog, for both knowledge representation and reasoning, and declarative problem solving.
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Handbook of Knowledge Representation, 1st Edition, 2008, Frank van Harmelen, Vladimir Lifschitz, Bruce Porter

  • Readership: graduates, researchers, software pactitioners, knowledge engineers
  • Handbook of Knowledge Representation describes the essential foundations of Knowledge Representation, which lies at the core of Artificial Intelligence (AI). The book provides an up-to-date review of twenty-five key topics in knowledge representation, written by the leaders of each field. It includes a tutorial background and cutting-edge developments, as well as applications of Knowledge Representation in a variety of AI systems.
  • Structure:
    • Part I deals with general methods in Knowledge Representation and reasoning and covers such topics as classical logic in Knowledge Representation; satisfiability solvers; description logics; constraint programming; conceptual graphs; nonmonotonic reasoning; model-based problem solving; and Bayesian networks.
    • Part II focuses on classes of knowledge and specialized representations, with chapters on temporal representation and reasoning; spatial and physical reasoning; reasoning about knowledge and belief; temporal action logics; and nonmonotonic causal logic.
    • Part III discusses Knowledge Representation in applications such as question answering; the semantic web; automated planning; cognitive robotics; multi-agent systems; and knowledge engineering.