Advances in Genetic Programming

Volume 3
Overview

Genetic programming is a form of evolutionary computation that evolves programs and program-like executable structures for developing reliable time—and cost-effective applications. It does this by breeding programs over many generations, using the principles of natural selection, sexual recombination, and mutuation. This third volume of Advances in Genetic Programming highlights many of the recent technical advances in this increasingly popular field.

Table of Contents

  1. Contributors
  2. Acknowledgments
  3. 1. An Introduction to the Third Volume

    Lee Spector, William B. Langdon, Una-May O'Reilly, Peter J. Angelino

  4. 2. An Automatic Software Re-Engineering Tool Based on Genetic Programming

    Conor Ryan and Laur Ivan

  5. 3. CAD Surface Reconstruction from Digitized 3D Point Data with a Genetic Programming/Evolution Strategy Hybrid

    Robert E. Keller, Wolfgang Banzhaf, Jörn Mehnen and Klaus Weinert

  6. 4. A Genetic Programming Approach for Robust Language Interpretation

    Carolyn Penstein Rosé

  7. 5. Time Series Modeling Using Genetic Programming: An Application to Rainfall-Runoff Models

    Peter A. Whigham and Peter F. Crapper

  8. 6. Automatic Synthesis, Placement, and Routing of Electrical Circuits by Means of Genetic Programming

    John R. Koza and Forest H. Bennett III

  9. 7. Quantum Computing Applications of Genetic Programming

    Lee Spector, Howard Barnum, Herbert J. Bernstein and Nikhil Swamy

  10. 8. The Evolution of Size and Shape

    William B. Langdon, Terry Soule, Riccardo Poli and James A. Foster

  11. 9. Fitness Distributions: Tools for Designing Efficient Evolutionary Computations

    Christian Igel and Kumar Chellapilla

  12. 10. Analysis of Single-Node (Building) Blocks in Genetic Programming

    Jason M. Daida, Robert R. Bertram, John A. Polito 2 and Stephen A. Stanhope

  13. 11. Rooted-Tree Schemata in Genetic Programming

    Justinian P. Rosca and Dana H. Ballard

  14. 12. Efficient Evolution of Machine Code for CISC Architectures Using Instruction Blocks and Homologous Crossover

    Peter Nordin, Wolfgang Banzhaf and Frank D. Francone

  15. 13. Sub-machine-code Genetic Programming

    Riccardo Poli and William B. Langdon

  16. 14. The Internal Reinforcement of Evolving Algorithms

    Astro Teller

  17. 15. Inductive Genetic Programming with Immune Network Dynamics

    Nikolay I. Nikolaev, Hitoshi Iba and Vanio Slavov

  18. 16. A Self-Tuning Mechanism for Depth-Dependent Crossover

    Takuyo Ito, Hitoshi Iba and Satoshi Sato

  19. 17. Genetic Recursive Regression for Modeling and Forecasting Real-World Chaotic Time Series

    Geum Yong Lee

  20. 18. Co-evolutionary Fitness Switching: Learning Complex Collective Behaviors Using Genetic Programming

    Byoung-Tak Zhang and Dong-Yeon Cho

  21. 19. Evolving Multiple Agents by Genetic Programming

    Hitoshi Iba

  22. Index