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Probabilistic Reasoning in Multiagent Systems : A Graphical Models Approach

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Title: Probabilistic Reasoning in Multiagent Systems : A Graphical Models Approach
Description: This 2002 book investigates the opportunities in building intelligent decision support systems offered by multi-agent distributed probabilistic reasoning. Probabilistic reasoning with graphical models, also known as Bayesian networks or belief networks, has become increasingly an active field of research and practice in artificial intelligence, operations research and statistics. The success of this technique in modeling intelligent decision support systems under the centralized and single-agent paradigm has been striking. Yang Xiang extends graphical dependence models to the distributed and multi-agent paradigm. He identifies the major technical challenges involved in such an endeavor and presents the results. The framework developed in the book allows distributed representation of uncertain knowledge on a large and complex environment embedded in multiple cooperative agents, and effective, exact and distributed probabilistic inference.
Authors: Yang Xiang
Resource Type: eBook.
Subjects: Intelligent agents (Computer software), Bayesian statistical decision theory, Distributed artificial intelligence, Bayesian statistical decision theory--Data processing
Categories: COMPUTERS / Business & Productivity Software / Business Intelligence, COMPUTERS / Artificial Intelligence / General
Database: eBook Collection (EBSCOhost)
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  – Type: ebook-pdf
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  Availability: 0
Header DbId: nlebk
DbLabel: eBook Collection (EBSCOhost)
An: 78385
RelevancyScore: 979
AccessLevel: 6
PubType: eBook
PubTypeId: ebook
PreciseRelevancyScore: 978.796813964844
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  Data: Probabilistic Reasoning in Multiagent Systems : A Graphical Models Approach
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  Label: Description
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  Data: This 2002 book investigates the opportunities in building intelligent decision support systems offered by multi-agent distributed probabilistic reasoning. Probabilistic reasoning with graphical models, also known as Bayesian networks or belief networks, has become increasingly an active field of research and practice in artificial intelligence, operations research and statistics. The success of this technique in modeling intelligent decision support systems under the centralized and single-agent paradigm has been striking. Yang Xiang extends graphical dependence models to the distributed and multi-agent paradigm. He identifies the major technical challenges involved in such an endeavor and presents the results. The framework developed in the book allows distributed representation of uncertain knowledge on a large and complex environment embedded in multiple cooperative agents, and effective, exact and distributed probabilistic inference.
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  Data: <searchLink fieldCode="AR" term="%22Yang+Xiang%22">Yang Xiang</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Intelligent+agents+%28Computer+software%29%22">Intelligent agents (Computer software)</searchLink><br /><searchLink fieldCode="DE" term="%22Bayesian+statistical+decision+theory%22">Bayesian statistical decision theory</searchLink><br /><searchLink fieldCode="DE" term="%22Distributed+artificial+intelligence%22">Distributed artificial intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Bayesian+statistical+decision+theory--Data+processing%22">Bayesian statistical decision theory--Data processing</searchLink>
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    Classifications:
      – Code: 006.3
        Scheme: ddc
        Type: prePub
    Languages:
      – Code: eng
        Text: English
    Subjects:
      – SubjectFull: Intelligent agents (Computer software)
        Type: general
      – SubjectFull: Bayesian statistical decision theory
        Type: general
      – SubjectFull: Distributed artificial intelligence
        Type: general
      – SubjectFull: Bayesian statistical decision theory--Data processing
        Type: general
    Titles:
      – TitleFull: Probabilistic Reasoning in Multiagent Systems : A Graphical Models Approach
        Type: main
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          Name:
            NameFull: Yang Xiang
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            NameFull: Yang Xiang
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          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2002
            – D: 04
              M: 02
              Type: profile
              Y: 2014
          Identifiers:
            – Type: isbn-print
              Value: 9780521813082
            – Type: isbn-electronic
              Value: 9780511020742
          Titles:
            – TitleFull: Probabilistic Reasoning in Multiagent Systems : A Graphical Models Approach
              Type: main
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