Swarm Intelligence (Hardcover)
內容描述
Traditional methods for creating intelligent computational systems
haveprivileged private "internal" cognitive and computational processes.
Incontrast, Swarm Intelligence argues that humanintelligence
derives from the interactions of individuals in a social worldand further,
that this model of intelligence can be effectively applied toartificially
intelligent systems. The authors first present the foundations ofthis new
approach through an extensive review of the critical literature insocial
psychology, cognitive science, and evolutionary computation. Theythen show
in detail how these theories and models apply to a newcomputational
intelligence methodology—particle swarms—which focuseson adaptation as the
key behavior of intelligent systems. Drilling downstill further, the authors
describe the practical benefits of applying particleswarm optimization to a
range of engineering problems. Developed bythe authors, this algorithm is an
extension of cellular automata andprovides a powerful optimization,
learning, and problem solving method.
This important book presents valuable new insights by exploring
theboundaries shared by cognitive science, social psychology, artificial
life,artificial intelligence, and evolutionary computation and by applying
theseinsights to the solving of difficult engineering problems. Researchers
andgraduate students in any of these disciplines will find the
materialintriguing, provocative, and revealing as will the curious and
savvycomputing professional.
Contents
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
