A Field Guide to Genetic Programming is an introduction to genetic programming (GP). GP is a systematic, domain-independent method for getting computers to solve problems automatically starting from a high-level statement of what needs to be done. Using ideas from natural evolution, GP starts from an ooze of random computer programs, and progressively refines them through processes of mutation and sexual recombination, until solutions emerge. All this without the user having to know or specify the form or structure of solutions in advance. GP has generated a plethora of human-competitive results and applications, including novel scientific discoveries and patentable inventions.
The book has a supporting web site.
- Title Page
- A Field Guide to Genetic Programming
- Copyright Page
- Preface
- Acknowledgements
- What’s in this book
- About the authors
- Dedication
- Chapter 1 - Introduction
- 1.1 Genetic Programming in a Nutshell
- 1.2 Getting Started
- 1.3 Prerequisites
- 1.4 Overview of this Field Guide
- Part I - Basics
- Chapter 2 - Representation, Initialisation and Operators in Tree-based GP
- Chapter 3 - Getting Ready to Run Genetic Programming
- Chapter 4 - Example Genetic Programming Run
- Part II - Advanced Genetic Programming
- Chapter 5 - Alternative Initialisations and Operators in Tree-based GP
- Chapter 6 - Modular, Grammatical and Developmental Tree-based GP
- Chapter 7 - Linear and Graph Genetic Programming
- Chapter 8 - Probabilistic Genetic Programming
- Chapter 9 - Multi-objective Genetic Programming
- Chapter 10 - Fast and Distributed Genetic Programming
- Chapter 11 - GP Theory and its Applications
- Part III - Practical Genetic Programming
- Chapter 12 - Applications
- Chapter 13 - Troubleshooting GP
- Chapter 14 - Conclusions
- Part IV - Tricks of the Trade
- Appendix A - Resources
- Appendix B - TinyGP
- Bibliography
- Index
- Colophon
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