Ebook: Evolution and Biocomputation: Computational Models of Evolution

This volume comprises ten thoroughly refereed and revised full papers originating from an interdisciplinary workshop on biocomputation entitled "Evolution as a Computational Process", held in Monterey, California in July 1992. This book is devoted to viewing biological evolution as a giant computational process being carried out over a vast spatial and temporal scale. Computer scientists, mathematicians and physicists may learn about optimization from looking at natural evolution and biologists may learn about evolution from studying artificial life, game theory, and mathematical optimization. In addition to the ten full papers addressing e.g. population genetics, emergence, artificial life, self-organization, evolutionary algorithms, and selection, there is an introductory survey and a subject index.

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This volume comprises ten thoroughly refereed and revised full papers originating from an interdisciplinary workshop on biocomputation entitled "Evolution as a Computational Process", held in Monterey, California in July 1992. This book is devoted to viewing biological evolution as a giant computational process being carried out over a vast spatial and temporal scale. Computer scientists, mathematicians and physicists may learn about optimization from looking at natural evolution and biologists may learn about evolution from studying artificial life, game theory, and mathematical optimization. In addition to the ten full papers addressing e.g. population genetics, emergence, artificial life, self-organization, evolutionary algorithms, and selection, there is an introductory survey and a subject index.

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This volume comprises ten thoroughly refereed and revised full papers originating from an interdisciplinary workshop on biocomputation entitled "Evolution as a Computational Process", held in Monterey, California in July 1992. This book is devoted to viewing biological evolution as a giant computational process being carried out over a vast spatial and temporal scale. Computer scientists, mathematicians and physicists may learn about optimization from looking at natural evolution and biologists may learn about evolution from studying artificial life, game theory, and mathematical optimization. In addition to the ten full papers addressing e.g. population genetics, emergence, artificial life, self-organization, evolutionary algorithms, and selection, there is an introductory survey and a subject index.
Content:
Front Matter....Pages -
Editors' introduction....Pages 1-6
Aspects of optimality behavior in population genetics theory....Pages 7-17
Optimization as a technique for studying population genetics equations....Pages 18-26
Emergence of mutualism....Pages 27-52
Three illustrations of artificial life's working hypothesis....Pages 53-68
Self-organizing algorithms derived from RNA interactions....Pages 69-102
Modeling the connection between development and evolution: Preliminary report....Pages 103-122
Soft genetic operators in Evolutionary Algorithms....Pages 123-141
Analysis of selection, mutation and recombination in genetic algorithms....Pages 142-168
The role of mate choice in biocomputation: Sexual selection as a process of search, optimization, and diversification....Pages 169-204
Genome growth and the evolution of the genotype-phenotype map....Pages 205-259
Back Matter....Pages -

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This volume comprises ten thoroughly refereed and revised full papers originating from an interdisciplinary workshop on biocomputation entitled "Evolution as a Computational Process", held in Monterey, California in July 1992. This book is devoted to viewing biological evolution as a giant computational process being carried out over a vast spatial and temporal scale. Computer scientists, mathematicians and physicists may learn about optimization from looking at natural evolution and biologists may learn about evolution from studying artificial life, game theory, and mathematical optimization. In addition to the ten full papers addressing e.g. population genetics, emergence, artificial life, self-organization, evolutionary algorithms, and selection, there is an introductory survey and a subject index.
Content:
Front Matter....Pages -
Editors' introduction....Pages 1-6
Aspects of optimality behavior in population genetics theory....Pages 7-17
Optimization as a technique for studying population genetics equations....Pages 18-26
Emergence of mutualism....Pages 27-52
Three illustrations of artificial life's working hypothesis....Pages 53-68
Self-organizing algorithms derived from RNA interactions....Pages 69-102
Modeling the connection between development and evolution: Preliminary report....Pages 103-122
Soft genetic operators in Evolutionary Algorithms....Pages 123-141
Analysis of selection, mutation and recombination in genetic algorithms....Pages 142-168
The role of mate choice in biocomputation: Sexual selection as a process of search, optimization, and diversification....Pages 169-204
Genome growth and the evolution of the genotype-phenotype map....Pages 205-259
Back Matter....Pages -
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