Genetic programming

This unique introduction to GP provides a detailed overview of the subject and its antecedents, with extensive references to the published and online literature. In addition to explaining the fundamental theory and important algorithms, the text includes practical discussions covering a wealth of potential applications and real-world implementation techniques. Software professionals needing to understand and apply GP concepts will find this book an invaluable practical and theoretical guide.

Table of contents :
Chapter 1 - Genetic Programming as Machine Learning
Chapter 2 - Genetic Programming and Biology
Chapter 3 - Computer Science and Mathematical Basics
Chapter 4 - Genetic Programming as Evolutionary Computation
Chapter 5 - Basic Concepts-The Foundation
Chapter 6 - Crossover-The Center of the Storm
Chapter 7 - Genetic Programming and Emergent Order
Chapter 8 - Analysis-Improving Genetic Programming with Statistics
Chapter 9 - Different Varieties of Genetic Programming
Chapter 10 - Advanced Genetic Programming
Chapter 11 - Implementation-Making Genetic Programming Work
Chapter 12 - Applications of Genetic Programming
Chapter 13 - Summary and Perspectives
Appendix A - Printed and Recorded Resources
Appendix B - Information Available on the Internet
Appendix C - GP Software
Appendix D - Events