Swarm Intelligence (eBook)

Russell C. Eberhart, James Kennedy, Yuhui Shi (Autoren)

eBook Download: PDF

2001 | 1. Auflage
512 Seiten
Elsevier Science (Verlag)
978-0-08-051826-8 (ISBN)

Infos

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.

Russ Eberhart is Associate Dean of Research at Purdue School of Engineering and Technology in Indianapolis, IN. He is the author of Neural Network PC Tools (Academic Press), a leading book in the field of Neural Networks. Among his credits, he is the former President of the IEEE Neural Networks Council.

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Traditional methods for creating intelligent computational systems have privileged private "e;internal"e; 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 intelligentadaptive behavior and evolutionary computation. * Describes recent results of experiments with the particle swarmoptimization (PSO) algorithm * Includes a basic overview of statistics to ensure readers canproperly analyze the results of their own experiments using thealgorithm. * Support software which can be downloaded from the publisherswebsite, includes a Java PSO applet, C and Visual Basic sourcecode.

Produkt-Details

• Erscheint lt. Verlag: 11.4.2001
• Sprache: englisch
• Themenwelt: Mathematik / Informatik ► Informatik ► Grafik / Design
• Themenwelt: Mathematik / Informatik ► Informatik ► Programmiersprachen / -werkzeuge
• Themenwelt: Informatik ► Theorie / Studium ► Algorithmen
• Themenwelt: Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
• Themenwelt: Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik
• ISBN-10: 0-08-051826-5 / 0080518265
• ISBN-13: 978-0-08-051826-8 / 9780080518268