Evolutionary Algorithms in Theory and Practice: Evolution Strategies, Evolutionary Programming, Genetic Algorithms
This book presents a unified view of evolutionary algorithms: the exciting new probabilistic search tools inspired by biological models that have immense potential as practical problem-solvers in a wide variety of settings, academic, commercial, and industrial. Get and download textbook Evolutionary Algorithms in Theory and Practice: Evolution Strategies, Evolutionary Programming, Genetic Algorithms for free
Evolutionary Algorithms in Theory and Practice Evolution Strategies, Evolutionary Programming, Genetic Algorithms, ISBN-13: 9780195099713, ISBN-10: 0195099710
In this work, the author compares the three most prominent representatives of evolutionary algorithms: genetic algorithms, evolution strategies, and evolutionary programming. The algorithms are presented within a unified framework, thereby clarifying the similarities and differences of these methods. The author also presents new results regarding the role of mutation and selection in genetic algorithms, showing how mutation seems to be much more important for the performance of genetic Evolutionary Algorithms in Theory and Practice new edition
Download free books for Evolutionary Algorithms in Theory and Practice
Evolutionary Algorithms in Theory and Practice: Thomas B?ck
author thomas back format hardback language english publication year 11 01 1996 subject computing it subject 2 computing textbooks study guides evolutionary algorithms in theory and practice evolution strategies evolution author s thomas back content note line figures tables country of publication united states date of publication 11 01 1996 first published 1996 format hardback genre level 1 adult non fiction specialist genre level 2 computing it genre level 3 computing textbooks study guides he
Evolutionary Algorithms in Theory and Practice: Thomas Baeck
"This book presents a unified view of evolutionary algorithms: the exciting new probabilistic search tools inspired by biological models that have immense potential as practical problem-solvers in a wide variety of settings, academic, commercial, and industrial. In this work, the author compares the three most prominent representatives of evolutionary algorithms: genetic algorithms, evolution strategies, and evolutionary programming. The algorithms are presented within a unified framework, thereby clarifying the similarities and differences of these methods. The author also presents new result
Evolutionary Algorithms in Theory and Practice Textbook
In this work, the author compares the three most prominent representatives of evolutionary algorithms: genetic algorithms, evolution strategies, and evolutionary programming
The author also presents new results regarding the role of mutation and selection in genetic algorithms, showing how mutation seems to be much more important for the performance of genetic
