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Adaptation in Natural and Artificial Systems: an Introductory Analysis with Applications to Biology Control and Artificial Intelligence

by John H Holland The MIT Press
Pub Date:
05/1992
ISBN:
9780262581110
Format:
Pbk 232 pages
Price:
AU$69.00 NZ$71.30
Product Status: Available in Approx 14 days
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A classic account of how complex systems (ranging from the weather, humans, biology, economics through to robots & computers) that seem to be chaotic are self organizing systems that evolve. Will be of interest to the many readers interested in 'chaos theory'. The author is a pioneering thinker who pioneered the field of Genetic Algorithms. 'the 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 or engineering such systems ignore Holland at their peril.' --David E. Goldberg , University of Illinois at Urbana-Champaign Genetic algorithms are playing an increasingly important role in studies of complex adaptive systems, ranging from adaptive agents in economic theory to the use of machine learning techniques in the design of complex devices such as aircraft turbines and integrated circuits. '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 the 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 or engineering such systems ignore Holland at their peril.' --David E. Goldberg , University of Illinois at Urbana-Champaign Genetic algorithms are playing an increasingly important role in studies of complex adaptive systems, ranging from adaptive agents in economic theory to the use of machine learning techniques in the design of complex devices such as aircraft turbines and integrated circuits. Adaptation in Natural and Artificial Systems is the book that intitiated this field of study, presenting the theoretical foundations and exploring applications y
Read this book, and even if you don't read it, buy it and display itproudly. Scientists, engineers, and coffee tables the world over should beinterested in the revised edition of this seminal book that first gathered anddeveloped the critical mass of ideas from mathematics, computational science, andsystems theory necessary to launch and fuel the ongoing revolution in complexinnovating systems. From mathematical optimization to the immune system, frommachine learning to the central nervous system, from automatic control systems toeven something as complex as human society itself, all innovating systems fall underthe spell of Holland's mathematical-computational magic, and all individualsinterested in understanding engineering such systems ignore Holland at theirperil. David E. Goldberg, Unviersity of Illinois-Champaign Adaptation by natural selection has many analogies with adaptive learningto the environment in the higher animals and in human individuals and society. Thepossibility of exploiting this analogy to solve problems and to model individual andsocial behavior has become greatly enhanced with the resources of modern computing.John Holland has brilliantly drawn the analogies with precise algorithmic accuracyand has analyzed the different levels of adaptation and their interrelation. Hismethods have been employed in studying economic interactions and have permitted areplication of the economy in terms of artificial adaptive agents learning newstrategies, an approach which permits us to see the effects of varying modes andcapacities for adaptation on the workings of the economy. Kenneth J. Arrow, Stanford University This book is required reading for anyone who is interested in theevolution of complex adaptive behavior. W. Danny Hillis, Thinking Machines Corporation Adaptation in Natural and Artificial Systems is a classic. It launchedthe entire field of genetic algorithms and was one of the principal inspiration forthe now-blossoming research area of Artificial Life. Douglas R. Hofstadter, Indiana University The last decade has seen a resurgence of interest in biologicalinspiration for parallel computing systems: first, the artificial neural networksinspired by study of the brain, and the genetic algorithms inspired by the study ofnatural selection and evolution. Inevitably, newcomers to the field are beginning tosuggest unifications. It will thus come as a delight to many to learn that JohnHolland's book...created the study of genetic algorithms within exactly such ainterdisciplinary perspective. Michael Arbib, University of Southern California John Holland is a modern seer. Over fifteen years ago...he conceived aunified framework for adaptation and from that invented the genetic algorithms whoseuse in engineering, science, and especially, contemporary artificial intelligenceand 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 andevolution. The MIT Press has performed a real service by making it available againto a wide audience. Charles E. Taylor, University of California, Los Angeles
John Holland is Professor of Psychology at the University of Michigan, Ann Arbor.