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Adaptation in Natural and Artificial Systems
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Table of Contents

Part 1 The general setting: preliminary survey; a simple artificial adaptive system; a complex natural adaptive system; some general observations. Part 2 A formal framework: discussion; presentation; comparison with the Dubins-Savage formalization of the gambler's problem. Part 3 Illustrations: genetics; economics; game-playing; searches, pattern recognition, and statistical inference; control and function optimization; central nervous systems. Part 4 Schemata. Part 5 The optimal allocation of trials: the 2-armed bandit; realization of minimal looses; many options; application to schemata. Part 6 Reproductive plans and genetic operators: generalized reproductive plans; generalized genetic operators - crossing-over; generalized genetic operators - inversion; generalized genetic operators - mutation; further increases in power; interpretations. Part 7 The robustness of genetic plans: adaptive plans; the robustness of plans; robustness vis-a-vis a simple artificial adaptive system; robustness vis-a-vis a complex and natural adaptive system; general consequence. Part 8 Adaptation of codings and representations: fixed representation; the "Broadcast Language"; usage; concerning applications and the use of genetic plans to modify representations. Part 9 An overview: insights; computer studies; advanced questions. Part 10 Interim and prospectus: in the interim; the optimal allocation of trials revisited; recent work; possibilities.

Promotional Information

Read this book, and even if you don't read it, buy it and display it proudly. Scientists, engineers, and coffee tables the world over should be interested in the revised edition of this seminal book that first gathered and developed the critical mass of ideas from mathematics, computational science, and systems theory necessary to launch and fuel the ongoing revolution in complex innovating systems. From mathematical optimization to the immune system, from machine learning to the central nervous system, from automatic control systems to even something as complex as human society itself, all innovating systems fall under the spell of Holland's mathematical-computational magic, and all individuals interested in understanding engineering such systems ignore Holland at their peril. -- David E. Goldberg, Unviersity of Illinois-Champaign Adaptation by natural selection has many analogies with adaptive learning to the environment in the higher animals and in human individuals and society. The possibility of exploiting this analogy to solve problems and to model individual and social behavior has become greatly enhanced with the resources of modern computing. John Holland has brilliantly drawn the analogies with precise algorithmic accuracy and has analyzed the different levels of adaptation and their interrelation. His methods have been employed in studying economic interactions and have permitted a replication of the economy in terms of artificial adaptive agents learning new strategies, an approach which permits us to see the effects of varying modes and capacities for adaptation on the workings of the economy. -- Kenneth J. Arrow, Stanford University This book is required reading for anyone who is interested in the evolution of complex adaptive behavior. -- W. Danny Hillis, Thinking Machines Corporation Adaptation in Natural and Artificial Systems is a classic. It launched the entire field of genetic algorithms and was one of the principal inspiration for the now-blossoming research area of Artificial Life. -- Douglas R. Hofstadter, Indiana University The last decade has seen a resurgence of interest in biological inspiration for parallel computing systems: first, the artificial neural networks inspired by study of the brain, and the genetic algorithms inspired by the study of natural selection and evolution. Inevitably, newcomers to the field are beginning to suggest unifications. It will thus come as a delight to many to learn that John Holland's book...created the study of genetic algorithms within exactly such a interdisciplinary perspective. -- Michael Arbib, University of Southern California John Holland is a modern seer. Over fifteen years ago...he conceived a unified framework for adaptation and from that invented the genetic algorithms whose use in engineering, science, and especially, contemporary artificial intelligence and artificial life has -- after a long gestation in which the rest of us caught up -- entered a phase of explosive growth. -- Stewart Wilson, Rowland Institute This book will be enjoyed by all students of population genetics and evolution. The MIT Press has performed a real service by making it available again to a wide audience. -- Charles E. Taylor, University of California, Los Angeles

About the Author

John H. Holland is Professor of Psychology and Professor of Computer Science and Engineering at the University of Michigan; he is also Trustee and External Professor at the Santa Fe Institute. He is the author of Hidden Order: How Adaptation Builds Complexity and other books.

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