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Foundations of Genetic ­Algorithms
9th International Workshop, FOGA 2007, Mexico City, Mexico, January 8-11, 2007, Revised Selected Papers (Lecture Notes in Computer Science) (Theoretical Computer Science and General Issues)
By Christopher R. Stephens (Edited by), Marc Toussaint (Edited by), Darrell Whitley (Edited by), Peter F. Stadler (Edited by)

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Format
Paperback, 216 pages
Published
Germany, 1 June 2007

Readers will find here a fascinating text that is the thoroughly refereed post-proceedings of the 9th Workshop on the Foundations of Genetic Algorithms, FOGA 2007, held in Mexico City in January 2007. The 11 revised full papers presented were carefully reviewed and selected during two rounds of reviewing and improvement from 22 submissions. The papers address all current topics in the field of theoretical evolutionary computation and also depict the continuing growth in interactions with other fields such as mathematics, physics, and biology


Inbreeding Properties of Geometric Crossover and Non-geometric Recombinations.- Just What Are Building Blocks?.- Sufficient Conditions for Coarse-Graining Evolutionary Dynamics.- On the Brittleness of Evolutionary Algorithms.- Mutative Self-adaptation on the Sharp and Parabolic Ridge.- Genericity of the Fixed Point Set for the Infinite Population Genetic Algorithm.- Neighborhood Graphs and Symmetric Genetic Operators.- Decomposition of Fitness Functions in Random Heuristic Search.- On the Effects of Bit-Wise Neutrality on Fitness Distance Correlation, Phenotypic Mutation Rates and Problem Hardness.- Continuous Optimisation Theory Made Easy? Finite-Element Models of Evolutionary Strategies, Genetic Algorithms and Particle Swarm Optimizers.- Saddles and Barrier in Landscapes of Generalized Search Operators.

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£45.01
Ships from UK Estimated delivery date: 11th Apr - 15th Apr from UK

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Product Description

Readers will find here a fascinating text that is the thoroughly refereed post-proceedings of the 9th Workshop on the Foundations of Genetic Algorithms, FOGA 2007, held in Mexico City in January 2007. The 11 revised full papers presented were carefully reviewed and selected during two rounds of reviewing and improvement from 22 submissions. The papers address all current topics in the field of theoretical evolutionary computation and also depict the continuing growth in interactions with other fields such as mathematics, physics, and biology


Inbreeding Properties of Geometric Crossover and Non-geometric Recombinations.- Just What Are Building Blocks?.- Sufficient Conditions for Coarse-Graining Evolutionary Dynamics.- On the Brittleness of Evolutionary Algorithms.- Mutative Self-adaptation on the Sharp and Parabolic Ridge.- Genericity of the Fixed Point Set for the Infinite Population Genetic Algorithm.- Neighborhood Graphs and Symmetric Genetic Operators.- Decomposition of Fitness Functions in Random Heuristic Search.- On the Effects of Bit-Wise Neutrality on Fitness Distance Correlation, Phenotypic Mutation Rates and Problem Hardness.- Continuous Optimisation Theory Made Easy? Finite-Element Models of Evolutionary Strategies, Genetic Algorithms and Particle Swarm Optimizers.- Saddles and Barrier in Landscapes of Generalized Search Operators.

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Product Details
EAN
9783540734796
ISBN
3540734791
Age Range
Other Information
X, 216 p.
Dimensions
23.4 x 16 x 1.4 centimeters (0.35 kg)

Table of Contents

Inbreeding Properties of Geometric Crossover and Non-geometric Recombinations.- Just What Are Building Blocks?.- Sufficient Conditions for Coarse-Graining Evolutionary Dynamics.- On the Brittleness of Evolutionary Algorithms.- Mutative Self-adaptation on the Sharp and Parabolic Ridge.- Genericity of the Fixed Point Set for the Infinite Population Genetic Algorithm.- Neighborhood Graphs and Symmetric Genetic Operators.- Decomposition of Fitness Functions in Random Heuristic Search.- On the Effects of Bit-Wise Neutrality on Fitness Distance Correlation, Phenotypic Mutation Rates and Problem Hardness.- Continuous Optimisation Theory Made Easy? Finite-Element Models of Evolutionary Strategies, Genetic Algorithms and Particle Swarm Optimizers.- Saddles and Barrier in Landscapes of Generalized Search Operators.

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