{"product_id":"b001iv75cg","title":"Swarm Intelligence (The Morgan Kaufmann Series in Evolutionary Computation)","description":"\u003cp\u003eTraditional methods for creating intelligent computational systems have\u003cbr\u003e\nprivileged private internal cognitive and computational processes. In\u003cbr\u003e\ncontrast,  Swarm Intelligence  argues that human\u003cbr\u003e\nintelligence derives from the interactions of individuals in a social world\u003cbr\u003e\nand further, that this model of intelligence can be effectively applied to\u003cbr\u003e\nartificially intelligent systems. The authors first present the foundations of\u003cbr\u003e\nthis new approach through an extensive review of the critical literature in\u003cbr\u003e\nsocial psychology, cognitive science, and evolutionary computation. They\u003cbr\u003e\nthen show in detail how these theories and models apply to a new\u003cbr\u003e\ncomputational intelligence methodology―particle swarms―which focuses\u003cbr\u003e\non adaptation as the key behavior of intelligent systems. Drilling down\u003cbr\u003e\nstill further, the authors describe the practical benefits of applying particle\u003cbr\u003e\nswarm optimization to a range of engineering problems. Developed by\u003cbr\u003e\nthe authors, this algorithm is an extension of cellular automata and\u003cbr\u003e\nprovides a powerful optimization, learning, and problem solving method.\u003c\/p\u003e\n\n\u003cp\u003eThis important book presents valuable new insights by exploring the\u003cbr\u003e\nboundaries shared by cognitive science, social psychology, artificial life,\u003cbr\u003e\nartificial intelligence, and evolutionary computation and by applying these\u003cbr\u003e\ninsights to the solving of difficult engineering problems. Researchers and\u003cbr\u003e\ngraduate students in any of these disciplines will find the material\u003cbr\u003e\nintriguing, provocative, and revealing as will the curious and savvy\u003cbr\u003e\ncomputing 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\u003c\/p\u003e","brand":"ANT","offers":[{"title":"Ebook","offer_id":67883058692341,"sku":"YSL28302","price":49.07,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/8774\/8597\/files\/413OWNUMR8L._SY1500.jpg?v=1793284261","url":"https:\/\/www.newbooks.store\/products\/b001iv75cg","provider":"NewBooks","version":"1.0","type":"link"}