Perspectives on Adaptation in Natural and Artificial SystemsLashon Booker, Stephanie Forrest, Melanie Mitchell, Rick Riolo This book is a collection of essays exploring adaptive systems from many perspectives, ranging from computational applications to models of adaptation in living and social systems. The essays on computation discuss history, theory, applications, and possible threats of adaptive and evolving computations systems. The modeling chapters cover topics such as evolution in microbial populations, the evolution of cooperation, and how ideas about evolution relate to economics. The title Perspectives on Adaptation in Natural and Artificial Systems honors John Holland, whose 1975 Book, Adaptation in Natural and Artificial Systems has become a classic text for many disciplines in which adaptation play a central role. The essays brought together here were originally written to honor John Holland, and span most of the different areas touched by his wide-ranging and influential research career. The authors include some of the most prominent scientists in the fields of artificial intelligence evolutionary computation, and complex adaptive systems. Taken together, these essays present a broad modern picture of current research on adaptation as it relates to computers, living systems, society, and their complex interactions. |
Contents
| 1 | |
| 9 | |
COMPUTATION ARTIFICIAL INTELLIGENCE AND BEYOND | 70 |
THE NATURAL WORLD AND BEYOND | 197 |
Index | 303 |
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Common terms and phrases
abstraction acetate Adaptation in Natural agents apply artificial intelligence Artificial Systems automatically behavior belief space best solution binary biological Booker Burks cells cellular automata chess circuit classifier clone cognitive complex adaptive systems component crossover culture developed DEVS discrete-event donation rate dynamic environments economic edited EDVAC electronic computer emergence empirical ENIAC equations equilibrium evolution evolutionary evolved example FIGURE filter fish fitness fitness landscape frequency Genetic Algorithms genetic programming glucose glycerol GOFAI human idea individuals influence function input interactions invention John Holland Koza Kurzweil learning logic machine machine learning mathematical mechanisms Moravec Morgan Kaufmann mutation Natural and Artificial Neumann neural neurons operators optimization output parameter patent patterns phase population predator predictions Press problem random Ray Kurzweil recombination representation Riolo robot Santa Fe Institute selection self-reproducing simple simulation situational knowledge solving structure tags theory tion topology variables