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Evolutionary Algorithms

Format Post in Mathematics BY Kenneth De Jong, L.Darrell Whitley, Lawrence D. Da

0387988262 Shared By Guest

Evolutionary Algorithms Kenneth De Jong, L.Darrell Whitley, Lawrence D. Da is available to download

Evolutionary Algorithms
Kenneth De Jong, L.Evolutionary Algorithms Textbook Darrell Whitley, Lawrence D. Davis, Michael D. Vose
Type: eBook
Released: 1999
Publisher: Springer
Page Count: 301
Format: pdf
Language: English
ISBN-10: 0387988262
ISBN-13: 9780387988269
The IMA Workshop on Evolutionary Algorithms brought together many of the top researchers in the area of Evolutionary Computation for a week of intensive interaction. The field of Evolutionary Computation has developed significantly over the past 30 years and today consists of a variety of subfields such as genetic algorithms, evolution strategies, evolutionary programming, and genetic programming, each with its own algorithmic perspectives and goals. The workshop did a great deal to clarify the current state of the theory of Evolutionary Algorithms. The existing theory might be characterized as deriving from two principal approaches. There is a high level macro-theory that looks at the processing of "building blocks" and "schemata" that are shared by many good solutions when searching a problem space. There is also a low level micro-theory that builds exact Markov models of the search process. It is sometimes hard for researchers working at such different levels of abstraction to interact. The IMA workshop allowed researchers working at these different levels to present their points of view and to move toward common ground. There was real progress in communication between theorists and practitioners in the evolutionary computation field. Speakers presented applications across a wide range of problem areas. In some of those cases, theoretically motivated methods work quite well. In other cases, practitioners used domain-based methods to obtain better performance than could be achieved by using a "pure" evolutionary algorithm. Individuals on both sides went away with a better appreciation of the successes and failures of current theory.

Evolutionary Algorithms

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