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Autor(en): 
  • James Kennedy
  • Yuhui Shi
  • Russell C Eberhart
  • Swarm Intelligence 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  März 2001  
    Genre:  EDV / Informatik 
     
    Künstliche Intelligenz, Künstliches Leben
    ISBN:  9781558605954 
    EAN-Code: 
    9781558605954 
    Verlag:  Elsevier Health Sciences 
    Einband:  Gebunden  
    Sprache:  English  
    Serie:  Morgan Kaufmann Series in Evol  
    Dimensionen:  H 242 mm / B 195 mm / D 30 mm 
    Gewicht:  1050 gr 
    Seiten:  544 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    Traditional methods for creating intelligent computational systems have
    privileged private "internal" cognitive and computational processes. In
    contrast, "Swarm Intelligence" argues that human
    intelligence derives from the interactions of individuals in a social world
    and further, that this model of intelligence can be effectively applied to
    artificially intelligent systems. The authors first present the foundations of
    this new approach through an extensive review of the critical literature in
    social psychology, cognitive science, and evolutionary computation. They
    then show in detail how these theories and models apply to a new
    computational intelligence methodologyparticle swarmswhich focuses
    on adaptation as the key behavior of intelligent systems. Drilling down
    still further, the authors describe the practical benefits of applying particle
    swarm optimization to a range of engineering problems. Developed by
    the authors, this algorithm is an extension of cellular automata and
    provides a powerful optimization, learning, and problem solving method.


    This important book presents valuable new insights by exploring the
    boundaries shared by cognitive science, social psychology, artificial life,
    artificial intelligence, and evolutionary computation and by applying these
    insights to the solving of difficult engineering problems. Researchers and
    graduate students in any of these disciplines will find the material
    intriguing, provocative, and revealing as will the curious and savvy
    computing professional.
    * Places particle swarms within the larger context of intelligent
    adaptive behavior and evolutionarycomputation.
    * Describes recent results of experiments with the particle swarm
    optimization (PSO) algorithm
    * Includes a basic overview of statistics to ensure readers can
    properly analyze the results of their own experiments using the
    algorithm.
    * Support software

      
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