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Artificial Evolution

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Cover of 'Artificial Evolution'

Table of Contents

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    Book Overview
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    Chapter 27 Evolution strategies: An alternative evolutionary algorithm
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    Chapter 28 An introduction to evolutionary programming
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    Chapter 29 An asymptotic theory for genetic algorithms
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    Chapter 30 Towards a genetic theory of easy and hard functions
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    Chapter 31 GAS, a concept on modeling species in genetic algorithms
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    Chapter 32 A genetic algorithm with parallel steady-state reproduction
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    Chapter 33 Induction-based control of genetic algorithms
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    Chapter 34 New multicriteria optimization method based on the use of a diploid genetic algorithm: Example of an industrial problem
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    Chapter 35 Lotka Volterra coevolution at the edge of chaos
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    Chapter 36 Evolution through cooperation: The Symbiotic Algorithm
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    Chapter 37 The artificial evolution of cooperation
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    Chapter 38 Immune system and fault-tolerant computing
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    Chapter 39 Modular genetic neural networks for 6-Legged locomotion
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    Chapter 40 An artificial life approach for the synthesis of autonomous agents
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    Chapter 41 How long does it take to evolve a neural net?
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    Chapter 42 Mixed IFS: Resolution of the inverse problem using genetic programming
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    Chapter 43 Interactive evolution for simulated natural evolution
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    Chapter 44 Building new tools for synthetic image animation by using evolutionary techniques
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    Chapter 45 A genetic algorithm with sharing for the detection of 2D geometric primitives in images
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    Chapter 46 A genetic algorithm to improve an Othello program
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    Chapter 47 A comparative study of a penalty function, a repair heuristic, and stochastic operators with the set-covering problem
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    Chapter 48 Study of genetic search for the Frequency Assignment Problem
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    Chapter 49 An application of evolutionary algorithms to the scheduling of robotic operations
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    Chapter 50 Genetic operators for two-dimentional shape optimization
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    Chapter 51 Air Traffic conflict resolution by Genetic Algorithms
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    Chapter 52 Optimizing hidden Markov models with a genetic algorithm
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Title
Artificial Evolution
Published by
Springer Berlin Heidelberg, January 2006
DOI 10.1007/3-540-61108-8
ISBNs
978-3-54-061108-0, 978-3-54-049948-0
Editors

Alliot, Jean-Marc, Lutton, Evelyne, Ronald, Edmund, Schoenauer, Marc, Snyers, Dominique

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The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 3 100%
Student > Doctoral Student 2 67%
Student > Bachelor 1 33%
Professor 1 33%
Researcher 1 33%
Other 1 33%
Readers by discipline Count As %
Computer Science 6 200%
Engineering 3 100%