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Theoretical Aspects of Evolutionary Computing

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Published by Springer Berlin Heidelberg in Berlin, Heidelberg .
Written in English

Subjects:

  • Biology,
  • Computer science,
  • Data processing,
  • Mathematics,
  • Artificial intelligence,
  • Operations research,
  • Computer software

Book details:

About the Edition

This book is the first in the field to provide extensive, entry level tutorials to the theory of Evolutionary Computing, covering the main approaches to understanding the dynamics of Evolutionary Algorithms. It combines this with recent, previously unpublished research papers based on the material of the tutorials. The outcome is a book which is self-contained to a large degree, attractive both to graduate students and researchers from other fields who want to get acquainted with the theory of Evolutionary Computing, and to active researchers in the field who can use this book as a reference and a source of recent results.

Edition Notes

Statementedited by Leila Kallel, Bart Naudts, Alex Rogers
SeriesNatural Computing Series, Natural Computing Series
ContributionsNaudts, Bart, Rogers, Alex
Classifications
LC ClassificationsQ334-342, TJ210.2-211.495
The Physical Object
Format[electronic resource] /
Pagination1 online resource (x, 499 p.)
Number of Pages499
ID Numbers
Open LibraryOL27091555M
ISBN 103642086764, 366204448X
ISBN 109783642086762, 9783662044483
OCLC/WorldCa851393991

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About this book During the first week of September , the Second EvoNet Summer School on Theoretical Aspects of Evolutionary Computing was held at the Middelheim cam­ pus of the University of Antwerp, Belgium. ISBN: OCLC Number: Notes: Based on the lectures and workshop contributions of the second EvoNet Summer School on Theoretical Aspects of Evolutionary Computing held at the Middelheim campus of the University of Antwerp, Belgium during the first week of September This book is the first in the field to provide extensive, entry level tutorials to the theory of Evolutionary Computing, covering the main approaches to understanding the dynamics of Evolutionary Algorithms. It combines this with recent, previously unpublished research papers based on the material of the tutorials. This book is based on the lectures and workshop contributions of this summer school. Its first part consists of tutorial papers which introduce the reader to a num ber of important directions in the theory of evolutionary computing. The tutorials are at graduate level andassume only a basic backgroundin mathematics and com puter science.

The term evolutionary computing (EC) refers to the study of the foundations and applications of certain heuristic techniques based on the principles of natural evolution, and thus the aim when designing evolutionary algorithms (EAs) is to mimic some of the processes taking place in natural evolution.   However, the theory on these algorithms is still in its infancy. Here it is discussed how and why such a theory should be developed. Afterwards, some fundamental results on evolutionary algorithms are presented in order to show how theoretical results on randomized search heuristics can be proved and how they contribute to the understanding of. During the first week of September , the Second EvoNet Summer School on Theoretical Aspects of Evolutionary Computing was held at the Middelheim cam pus of the University of Antwerp, Belgium. Originally intended as a small get together of PhD students interested in the theory of evolutionary computing, the summer school grew to become a successful combination of a four-day workshop . About this book The term evolutionary computing (EC) refers to the study of the foundations and applications of certain heuristic techniques based on the principles of natural evolution, and thus the aim when designing evolutionary algorithms (EAs) is to mimic some of the processes taking place in natural evolution.

Buy Theoretical Aspects of Evolutionary Computing on FREE SHIPPING on qualified orders Theoretical Aspects of Evolutionary Computing: Kallel, Leila, Naudts, Bart, Rogers, Alex: : Books. Evolutionary algorithms is a class of randomized heuristics inspired by natural evolution. They are applied in many different contexts, in particular in optimization, and analysis of such algorithms has seen tremendous advances in recent years. In this book the author provides an introduction to. The book then describes theoretical results on three important questions in evolutionary computation: how to profit from changing the parameters during the run of an algorithm; how evolutionary algorithms cope with dynamically changing or stochastic environments; and . Evolutionary algorithms form a subset of evolutionary computation in that they generally only involve techniques implementing mechanisms inspired by biological evolution such as reproduction, mutation, recombination, natural selection and survival of the fittest. Candidate solutions to the optimization problem play the role of individuals in a population, and the cost function determines the.