Evolutionary Computation: Theory And Applications
eBook - PDF

Evolutionary Computation: Theory And Applications

  1. 376 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

Evolutionary Computation: Theory And Applications

About this book

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.

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Yes, you can access Evolutionary Computation: Theory And Applications by Xin Yao in PDF and/or ePUB format, as well as other popular books in Computer Science & Artificial Intelligence (AI) & Semantics. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Contents
  2. Preface
  3. Acknowledgements
  4. List of Contributors
  5. Chapter 1 Introduction
  6. Chapter 2 Evolutionary Computation in Behavior Engineering
  7. Chapter 3 A General Method for Incremental Self-improvement and Multi-agent Learning
  8. Chapter 4 Teacher: A Genetics-Based System for Learning and for Generalizing Heuristics
  9. Chapter 5 Automatic Discovery of Protein Motifs Using Genetic Programming
  10. Chapter 6 The Role of Self Organization in Evolutionary Computations
  11. Chapter 7 Virus-Evolutionary Genetic Algorithm and Its Application to Traveling Salesman Problem
  12. Chapter 8 Hybrid Evolutionary Optimization Algorithm for Constrained Problems
  13. Chapter 9 CAM-BRAIN — The Evolutionary Engineering of a Billion Neuron Artificial Brain
  14. Chapter 10 An Evolutionary Approach to the N-Player Iterated Prisoner's Dilemma Game
  15. Index