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Illustrating evolutionary computation with Mathematica /

An essential capacity of intelligence is the ability to learn. An artificially intelligent system that could learn would not have to be programmed for every eventuality; it could adapt to its changing environment and conditions just as biological systems do. Illustrating Evolutionary Computation wit...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Jacob, Christian
Formato: Electrónico eBook
Idioma:Inglés
Alemán
Publicado: San Francisco : Morgan Kaufmann Pub., ©2001.
Colección:Evolutionary Computation Ser.
Temas:
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)

MARC

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240 1 0 |a Principia evolvica.  |l English 
245 1 0 |a Illustrating evolutionary computation with Mathematica /  |c Christian Jacob ; translated from the German by Christian Jacob. 
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490 1 |a Evolutionary Computation Ser. 
504 |a Includes bibliographical references (pages 527-546) and index. 
588 0 |a Print version record. 
505 0 |a Part 1: Fascinating Evolution -- Part 2: Evolutionary Computation -- Part 3: If Darwin was a Programmer -- Part 4: Evolution of Developmental Programs. 
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520 |a An essential capacity of intelligence is the ability to learn. An artificially intelligent system that could learn would not have to be programmed for every eventuality; it could adapt to its changing environment and conditions just as biological systems do. Illustrating Evolutionary Computation with Mathematica introduces evolutionary computation to the technically savvy reader who wishes to explore this fascinating and increasingly important field. Unique among books on evolutionary computation, the book also explores the application of evolution to developmental processes in nature, such as the growth processes in cells and plants. If you are a newcomer to the evolutionary computation field, an engineer, a programmer, or even a biologist wanting to learn how to model the evolution and coevolution of plants, this book will provide you with a visually rich and engaging account of this complex subject. * Introduces the major mechanisms of biological evolution. * Demonstrates many fascinating aspects of evolution in nature with simple, yet illustrative examples. * Explains each of the major branches of evolutionary computation: genetic algorithms, genetic programming, evolutionary programming, and evolution strategies. * Demonstrates the programming of computers by evolutionary principles using Evolvica, a genetic programming system designed by the author. * Shows in detail how to evolve developmental programs modeled by cellular automata and Lindenmayer systems. * Provides Mathematica notebooks on the Web that include all the programs in the book and supporting animations, movies, and graphics. 
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650 0 |a Evolutionary computation. 
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