Foundations Of Genetic Algorithms 1993 Foga 2

Author: FOGA
Publisher: Morgan Kaufmann
ISBN: 0080948324
Size: 13.59 MB
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Foundations Of Genetic Algorithms 1993 Foga 2 from the Author: FOGA. Foundations of Genetic Algorithms, Volume 2 provides insight of theoretical work in genetic algorithms. This book provides a general understanding of a canonical genetic algorithm. Organized into six parts encompassing 19 chapters, this volume begins with an overview of genetic algorithms in the broader adaptive systems context. This text then reviews some results in mathematical genetics that use probability distributions to characterize the effects of recombination on multiple loci in the absence of selection. Other chapters examine the static building block hypothesis (SBBH), which is the underlying assumption used to define deception. This book discusses as well the effect of noise on the quality of convergence of genetic algorithms. The final chapter deals with the primary goal in machine learning and artificial intelligence, which is to dynamically and automatically decompose problems into simpler problems to facilitate their solution. This book is a valuable resource for theorists and genetic algorithm researchers.

Foundations Of Genetic Algorithms 2

Author: L. Darrell Whitley
Publisher: Morgan Kaufmann
ISBN:
Size: 17.36 MB
Format: PDF, Kindle
View: 6922
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Foundations Of Genetic Algorithms 2 from the Author: L. Darrell Whitley. Foundations of Genetic Algorithms, Volume 2 provides insight of theoretical work in genetic algorithms. This book provides a general understanding of a canonical genetic algorithm. Organized into six parts encompassing 19 chapters, this volume begins with an overview of genetic algorithms in the broader adaptive systems context. This text then reviews some results in mathematical genetics that use probability distributions to characterize the effects of recombination on multiple loci in the absence of selection. Other chapters examine the static building block hypothesis (SBBH), which is the underlying assumption used to define deception. This book discusses as well the effect of noise on the quality of convergence of genetic algorithms. The final chapter deals with the primary goal in machine learning and artificial intelligence, which is to dynamically and automatically decompose problems into simpler problems to facilitate their solution. This book is a valuable resource for theorists and genetic algorithm researchers.

Foundations Of Genetic Algorithms 1991 Foga 1

Author: FOGA
Publisher: Morgan Kaufmann
ISBN: 0080506844
Size: 16.49 MB
Format: PDF, ePub, Docs
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Foundations Of Genetic Algorithms 1991 Foga 1 from the Author: FOGA. Foundations of Genetic Algorithms 1991 (FOGA 1) discusses the theoretical foundations of genetic algorithms (GA) and classifier systems. This book compiles research papers on selection and convergence, coding and representation, problem hardness, deception, classifier system design, variation and recombination, parallelization, and population divergence. Other topics include the non-uniform Walsh-schema transform; spurious correlations and premature convergence in genetic algorithms; and variable default hierarchy separation in a classifier system. The grammar-based genetic algorithm; conditions for implicit parallelism; and analysis of multi-point crossover are also elaborated. This text likewise covers the genetic algorithms for real parameter optimization and isomorphisms of genetic algorithms. This publication is a good reference for students and researchers interested in genetic algorithms.

Machine Learning

Author: Armand Prieditis
Publisher: Morgan Kaufmann
ISBN: 9781558603776
Size: 39.82 MB
Format: PDF
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Machine Learning from the Author: Armand Prieditis.

An Introduction To Genetic Algorithms

Author: Melanie Mitchell
Publisher: MIT Press
ISBN: 9780262631853
Size: 22.14 MB
Format: PDF
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An Introduction To Genetic Algorithms from the Author: Melanie Mitchell. Genetic algorithms are used in science and engineering for problem solving and as computational models. This brief introduction enables readers to implement and experiment with genetic algorithms on their own. The descriptions of applications and modeling projects stretch beyond the boundaries of computer science to include systems theory, game theory, biology, ecology, and population genetics. 20 illustrations.

Gecco 2000

Author: L. Darrell Whitley
Publisher: Morgan Kaufmann Pub
ISBN:
Size: 61.18 MB
Format: PDF, Kindle
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Gecco 2000 from the Author: L. Darrell Whitley.

Genetic Programming

Author: John R. Koza
Publisher: Morgan Kaufmann Pub
ISBN: 9781558605480
Size: 25.86 MB
Format: PDF
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Genetic Programming from the Author: John R. Koza. Proceedings of the Annual Conferences on Genetic Programming. These proceedings present the most recent research in the field of genetic programming as well as recent research results in the fields of genetic algorithms, artificial life and evolution strategies, DNA computing, evolvable hardware, and genetic learning classifier systems.

Ieee International Conference On Evolutionary Computation

Author: IEEE Neural Networks Council
Publisher:
ISBN: 9780780348691
Size: 39.47 MB
Format: PDF, Docs
View: 3000
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Ieee International Conference On Evolutionary Computation from the Author: IEEE Neural Networks Council. This conference covers a wide range of aspects of evolutionary computing. This includes principles of evolutionary computation such as adaptation and self-adaption, variation operators, representational issues, and theoretical investigations.