Advances in genetic programming. Volume III

Advances in genetic programming. Volume III / edited by Lee Spector, William B. Langdon, Una-May O'Reilly.

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 recombinati...

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Bibliographic Details
Other Authors: Spector, Lee (Editor), Langdon, William B. (Editor), O'Reilly, Una-May (Editor)
Format: eBook
Language:English
Published: Cambridge, Mass. : MIT Press, [1999]
Series:Complex adaptive systems.
Subjects:
Genetic programming (Computer science)
COMPUTERS > Enterprise Applications > Business Intelligence Tools.
COMPUTERS > Intelligence (AI) & Semantics.
Computadores (software)
Online Access:Click for online access
Table of Contents:
  • Contributors
  • Acknowledgments
  • 1. An Introduction to the Third Volume / 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 / Conor Ryan and Laur Ivan
  • 3. CAD Surface Reconstruction from Digitized 3D Point Data with a Genetic Programming/Evolution Strategy Hybrid / Robert E. Keller, Wolfgang Banzhaf, Jorn Mehnen and Klaus Weinert
  • 4. A Genetic Programming Approach for Robust Language Interpretation / Carolyn Penstein Rose
  • 5. Time Series Modeling Using Genetic Programming: An Application to Rainfall-Runoff Models / Peter A. Whigham and Peter F. Crapper
  • 6. Automatic Synthesis, Placement, and Routing of Electrical Circuits by Means of Genetic Programming / John R. Koza and Forest H. Bennett III
  • 7. Quantum Computing Applications of Genetic Programming / Lee Spector, Howard Barnum, Herbert J. Bernstein and Nikhil Swamy
  • II. Theory
  • II. Theory
  • 8. The Evolution of Size and Shape / William B. Langdon, Terry Soule, Riccardo Poli and James A. Foster
  • 9. Fitness Distributions: Tools for Designing Efficient Evolutionary Computations / Christian Igel and Kumar Chellapilla
  • 10. Analysis of Single-Node (Building) Blocks in Genetic Programming / Jason M. Daida, Robert R. Bertram, John A. Polito 2 and Stephen A. Stanhope
  • 11. Rooted-Tree Schemata in Genetic Programming / 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 / Peter Nordin, Wolfgang Banzhaf and Frank D. Francone
  • 13. Sub-machine-code Genetic Programming / Riccardo Poli and William B. Langdon
  • 14. The Internal Reinforcement of Evolving Algorithms / Astro Teller
  • 15. Inductive Genetic Programming with Immune Network Dynamics / Nikolay I. Nikolaev, Hitoshi Iba and Vanio Slavov
  • 16. A Self-Tuning Mechanism for Depth-Dependent Crossover / Takuyo Ito, Hitoshi Iba and Satoshi Sato
  • 17. Genetic Recursive Regression for Modeling and Forecasting Real-World Chaotic Time Series / Geum Yong Lee
  • 18. Co-evolutionary Fitness Switching: Learning Complex Collective Behaviors Using Genetic Programming / Byoung-Tak Zhang and Dong-Yeon Cho
  • 19. Evolving Multiple Agents by Genetic Programming / Hitoshi Iba
  • Index.

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