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Swarm Intelligence by James Kennedy, et al Sales Rank : 52,665

Hardcover: 510 pages Publisher: Morgan Kaufmann; 1st edition March 23, 2001 ISBN: 1558605959 Product Dimensions: 9.6 x 7.6 x 1.2 inches Shipping Weight: 2.4 pounds. Average Customer Review: based on 11 reviews. From Book News, Inc. Particle swarm optimization (PSO) is a new kind of social intelligence model. This interdisciplinary work places particle swarms within the larger context of intelligent adaptive behavior and evolutionary computation, drawing on findings in social-psychological and engineering research to derive a set of optimization algorithms that shed light on human information processing and provide tools for numerical and qualitative optimization. Of interest to researchers and graduate students in cognitive, social, and computer science. Kennedy is a social psychologist who works in survey methods at the US Department of Labor. He has worked with the particle swarm computer model of social influence in artificial communities since 1994.Copyright © 2004 Book News, Inc., Portland, OR Product 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 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.

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