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Introduction to evolutionary computing

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Introduction to evolutionary computing/ by A.E. Eiben, J.E. Smith.
Author:	Eiben, Agoston E.
other author:	Smith, J. E.
Published:	Berlin, Heidelberg :Springer Berlin Heidelberg : : 2015.,
Description:	xii, 287 p. :ill., digital ; : 24 cm.;
Contained By:	Springer eBooks
Subject:	Evolutionary programming (Computer science) -
Online resource:	http://dx.doi.org/10.1007/978-3-662-44874-8
ISBN:	9783662448748 (electronic bk.)

Introduction to evolutionary computing
Eiben, Agoston E.

Introduction to evolutionary computing[electronic resource] /by A.E. Eiben, J.E. Smith. - 2nd ed. - Berlin, Heidelberg :Springer Berlin Heidelberg :2015. - xii, 287 p. :ill., digital ;24 cm. - Natural computing series,1619-7127. - Natural computing series..

Problems to Be Solved -- Evolutionary Computing: The Origins -- What Is an Evolutionary Algorithm? -- Representation, Mutation, and Recombination -- Fitness, Selection, and Population Management -- Popular Evolutionary Algorithm Variants -- Hybridisation with Other Techniques: Memetic Algorithms -- Nonstationary and Noisy Function Optimisation -- Multiobjective Evolutionary Algorithms -- Constraint Handling -- Interactive Evolutionary Algorithms -- Coevolutionary Systems -- Theory -- Evolutionary Robotics -- Parameters and Parameter Tuning -- Parameter Control -- Working with Evolutionary Algorithms -- References.

The overall structure of this new edition is three-tier: Part I presents the basics, Part II is concerned with methodological issues, and Part III discusses advanced topics. In the second edition the authors have reorganized the material to focus on problems, how to represent them, and then how to choose and design algorithms for different representations. They also added a chapter on problems, reflecting the overall book focus on problem-solvers, a chapter on parameter tuning, which they combined with the parameter control and "how-to" chapters into a methodological part, and finally a chapter on evolutionary robotics with an outlook on possible exciting developments in this field. The book is suitable for undergraduate and graduate courses in artificial intelligence and computational intelligence, and for self-study by practitioners and researchers engaged with all aspects of bioinspired design and optimization.

ISBN: 9783662448748 (electronic bk.)

Standard No.: 10.1007/978-3-662-44874-8doiSubjects--Topical Terms:

573186
Evolutionary programming (Computer science)

LC Class. No.: QA76.618

Dewey Class. No.: 006.3823

Introduction to evolutionary computing
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505 0 $a Problems to Be Solved -- Evolutionary Computing: The Origins -- What Is an Evolutionary Algorithm? -- Representation, Mutation, and Recombination -- Fitness, Selection, and Population Management -- Popular Evolutionary Algorithm Variants -- Hybridisation with Other Techniques: Memetic Algorithms -- Nonstationary and Noisy Function Optimisation -- Multiobjective Evolutionary Algorithms -- Constraint Handling -- Interactive Evolutionary Algorithms -- Coevolutionary Systems -- Theory -- Evolutionary Robotics -- Parameters and Parameter Tuning -- Parameter Control -- Working with Evolutionary Algorithms -- References.
520 $a The overall structure of this new edition is three-tier: Part I presents the basics, Part II is concerned with methodological issues, and Part III discusses advanced topics. In the second edition the authors have reorganized the material to focus on problems, how to represent them, and then how to choose and design algorithms for different representations. They also added a chapter on problems, reflecting the overall book focus on problem-solvers, a chapter on parameter tuning, which they combined with the parameter control and "how-to" chapters into a methodological part, and finally a chapter on evolutionary robotics with an outlook on possible exciting developments in this field. The book is suitable for undergraduate and graduate courses in artificial intelligence and computational intelligence, and for self-study by practitioners and researchers engaged with all aspects of bioinspired design and optimization.
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