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Swarm Intelligence,

Edition 1

Editors: By Russell C. Eberhart, Yuhui Shi and James Kennedy

Publication Date: 26 Mar 2001

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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.

Key Features

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

About the author

By Russell C. Eberhart, Purdue School of Engineering; Yuhui Shi, Electronic Data Systems, Inc. and James Kennedy, US Department of Labor

Introduction

Part 1: Foundations
Life and Intelligence
Optimization by Trial and Error
On our Nonexistence as Entities
Evolutionary Computation Theory and Paradigms
Humans - Actual, Imagined and Implied
Thinking is Social

Part 2: Particle Optimization and Collective Intelligence
The Binary Particle Swarm
Variations and Comparisons;
Applications
Implications and Speculations
Conclusions