Swarm Intelligence Ebook

Publication: Morgan Kaufmann
 
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Language: English
Publication Date: April 2001
File Size: 6391 Kbytes

Restrictions set by Publisher:
- Text-to-speech feature not available.
- Printing is permitted.
- You can copy text from file.
- Free application Adobe Digital Editions, Aldiko reader, or Bluefire reader required .
$111.15 $118.00
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ISBN: 9780080518268   Should I buy this Ebook?   Write a Review

Description

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 methodology-particle swarms-which 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 evolutionary computation.
  • 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 which can be downloaded from the publishers
    website, includes a Java PSO applet, C and Visual Basic source
    code.

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Swarm Intelligence