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Jul 1999
ISBN 0262194236
488 pp.
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Advances in Genetic Programming - Vol. 3
Lee Spector , William B. Langdon , Una-May O'Reilly and PeterJ

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
 Contributors
 Acknowledgments
1 An Introduction to the Third Volume
by Lee Spector, William B. Langdon, Una-May O'Reilly, Peter J. Angelino
I Applications
2 An Automatic Software Re-Engineering Tool Based on Genetic Programming
by Conor Ryan and Laur Ivan
3 CAD Surface Reconstruction from Digitized 3D Point Data with a Genetic Programming/Evolution Strategy Hybrid
by Robert E. Keller, Wolfgang Banzhaf, Jörn Mehnen and Klaus Weinert
4 A Genetic Programming Approach for Robust Language Interpretation
by Carolyn Penstein Rosé
5 Time Series Modeling Using Genetic Programming: An Application to Rainfall-Runoff Models
by Peter A. Whigham and Peter F. Crapper
6 Automatic Synthesis, Placement, and Routing of Electrical Circuits by Means of Genetic Programming
by John R. Koza and Forest H. Bennett III
7 Quantum Computing Applications of Genetic Programming
by Lee Spector, Howard Barnum, Herbert J. Bernstein and Nikhil Swamy
II Theory
II Theory
8 The Evolution of Size and Shape
by William B. Langdon, Terry Soule, Riccardo Poli and James A. Foster
9 Fitness Distributions: Tools for Designing Efficient Evolutionary Computations
by Christian Igel and Kumar Chellapilla
10 Analysis of Single-Node (Building) Blocks in Genetic Programming
by Jason M. Daida, Robert R. Bertram, John A. Polito 2 and Stephen A. Stanhope
11 Rooted-Tree Schemata in Genetic Programming
by Justinian P. Rosca and Dana H. Ballard
III Extensions
III Extensions
12 Efficient Evolution of Machine Code for CISC Architectures Using Instruction Blocks and Homologous Crossover
by Peter Nordin, Wolfgang Banzhaf and Frank D. Francone
13 Sub-machine-code Genetic Programming
by Riccardo Poli and William B. Langdon
14 The Internal Reinforcement of Evolving Algorithms
by Astro Teller
15 Inductive Genetic Programming with Immune Network Dynamics
by Nikolay I. Nikolaev, Hitoshi Iba and Vanio Slavov
16 A Self-Tuning Mechanism for Depth-Dependent Crossover
by Takuyo Ito, Hitoshi Iba and Satoshi Sato
17 Genetic Recursive Regression for Modeling and Forecasting Real-World Chaotic Time Series
by Geum Yong Lee
18 Co-evolutionary Fitness Switching: Learning Complex Collective Behaviors Using Genetic Programming
by Byoung-Tak Zhang and Dong-Yeon Cho
19 Evolving Multiple Agents by Genetic Programming
by Hitoshi Iba
 Index
 
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