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    UNCERTAINTY AND INTELLIGENT INFORMATION SYSTEMS

    edited by Bernadette Bouchon-Meunier (Université Pierre et Marie Curie-Paris 6, France), Christophe Marsala (Université Pierre et Marie Curie-Paris 6, France), Maria Rifqi (Université Pierre et Marie Curie-Paris 6, France), & Ronald R Yager (Iona College, USA)

    Table of Contents (93k)
    Foreword (58k)
    Chapter 1: The Game-Theoretic Framework for Probability (2,147k)

    Intelligent systems are necessary to handle modern computer-based technologies managing information and knowledge. This book discusses the theories required to help provide solutions to difficult problems in the construction of intelligent systems. Particular attention is paid to situations in which the available information and data may be imprecise, uncertain, incomplete or of a linguistic nature. The main aspects of clustering, classification, summarization, decision making and systems modeling are also addressed. Topics covered in the book include fundamental issues in uncertainty, the rapidly emerging discipline of information aggregation, neural networks, Bayesian networks and other network methods, as well as logic-based systems.

     
    Contents:
    • Uncertainty Modeling
    • Clustering, Classification and Summarization
    • Decision Making and Information Processing
    • Systems Modeling and Applications
    • Logic and Mathematical Structures
     
    Readership: Academics, graduate and postgraduate students in the fields of artificial intelligence and fuzzy logic.
     
     
    536pp    Pub. date: Jul 2008  
    ISBN:   978-981-279-234-1
    981-279-234-1
       US$205 / £135

     


    536pp    Pub. date: Jul 2008  
    ISBN:   978-981-279-235-8(ebook)
    981-279-235-X(ebook)
       US$267

     


     

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    Updated on 10 February 2012