Swarm Intelligence argues that intelligent human cognition derives from the interactions of individuals in a social world and that the sociocognitive view can be effectively applied to computationally intelligent systems. This interdisciplinary work draws on findings in social-psychological and engineering research to derive a family of optimization algorithms that shed light on human information processing as well as providing tools for numerical and qualitative optimization. Particle swarm optimization (PSO) is an entirely new kind of social intelligence model to be recast as an optimization, learning, and problem solving method, thus establishing its importance as a milestone.

This important book presents valuable new insights by exploring interdisciplinary boundaries and by applying these insights to the solving of difficult engineering problems. Researchers and graduate students in social and computer science will find the material intriguing, provocative, and revealing, as will the savvy computing professional.

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