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E-raamat: Evolutionary Computation: Theory And Applications

Edited by (Univ Of Birmingham, Uk)
  • Formaat: 376 pages
  • Ilmumisaeg: 22-Nov-1999
  • Kirjastus: World Scientific Publishing Co Pte Ltd
  • Keel: eng
  • ISBN-13: 9789814518161
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Evolutionary Computation: Theory And ApplicationsSuurem pilt
  • Formaat: 376 pages
  • Ilmumisaeg: 22-Nov-1999
  • Kirjastus: World Scientific Publishing Co Pte Ltd
  • Keel: eng
  • ISBN-13: 9789814518161
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Evolutionary computation is the study of computational systems which use ideas and get inspiration from natural evolution and adaptation. This book is devoted to the theory and application of evolutionary computation. It is a self-contained volume which covers both introductory material and selected advanced topics. The book can roughly be divided into two major parts: the introductory one and the one on selected advanced topics. Each part consists of several chapters which present an in-depth discussion of selected topics. A strong connection is established between evolutionary algorithms and traditional search algorithms. This connection enables us to incorporate ideas in more established fields into evolutionary algorithms. The book is aimed at a wide range of readers. It does not require previous exposure to the field since introductory material is included. It will be of interest to anyone who is interested in adaptive optimization and learning. People in computer science, artificial intelligence, operations research, and various engineering fields will find it particularly interesting.
Preface v Acknowledgements vii List of Contributors ix Introduction 1(36) X. Yao Evolutionary Computation in Behavior Engineering 37(44) M. Colombetti M. Dorigo A General Method for Incremental Self-improvement and Multi-agent Learning 81(43) J. Schmidhuber Teacher: A Genetics-Based System for Learning and for Generalizing Heuristics 124(47) B.W. Wah A. Ieumwananonthachai Automatic Discovery of Protein Motifs Using Genetic Programming 171(27) J.R. Koza D. Andre The Role of Self Organization in Evolutionary Computations 198(37) A.C. Tsoi J. Shaw Virus-Evolutionary Genetic Algorithm and Its Application to Traveling Salesman Problem 235(21) T. Fukuda N. Kubota K. Shimojima Hybrid Evolutionary Optimization Algorithm for Constrained Problems 256(40) J.-H. Kim H. Myung CAM-BRAIN--The Evolutionary Engineering of a Billion Neuron Artificial Brain 296(35) H. de Garis An Evolutionary Approach to the N-Player Iterated Prisoners Dilemma Game 331(28) X. Yao P. Darwen Index 359
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