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© 2011

Genetic Programming Theory and Practice VIII

  • Rick Riolo
  • Trent McConaghy
  • Ekaterina Vladislavleva
Book

Part of the Genetic and Evolutionary Computation book series (GEVO, volume 8)

Table of contents

  1. Front Matter
    Pages 1-1
  2. Michael Orlov, Moshe Sipper
    Pages 1-16
  3. Peter Lichodzijewski, Malcolm Heywood
    Pages 35-54
  4. Terence Soule, Robert B. Heckendorn, Brian Dyre, Roger Lew
    Pages 55-69
  5. Simon Harding, Wolfgang Banzhaf, Julian F. Miller
    Pages 91-107
  6. Michael F. Korns
    Pages 109-128
  7. Michael Schmidt, Hod Lipson
    Pages 129-146
  8. Guido F. Smits, Ekaterina Vladislavleva, Mark E. Kotanchek
    Pages 147-160
  9. Flor Castillo, Arthur Kordon, Carlos Villa
    Pages 175-194
  10. Kristine A. Pattin, Joshua L. Payne, Douglas P. Hill, Thomas Caldwell, Jonathan M. Fisher, Jason H. Moore
    Pages 195-210
  11. Steven Bergen, Brian J. Ross
    Pages 227-244
  12. Back Matter
    Pages 16-16

About this book

Introduction

The contributions in this volume are written by the foremost international researchers and practitioners in the GP arena. They examine the similarities and differences between theoretical and empirical results on real-world problems. The text explores the synergy between theory and practice, producing a comprehensive view of the state of the art in GP application.

Topics include: FINCH: A System for Evolving Java, Practical Autoconstructive Evolution, The Rubik Cube and GP Temporal Sequence Learning, Ensemble classifiers: AdaBoost and Orthogonal Evolution of Teams, Self-modifying Cartesian GP, Abstract Expression Grammar Symbolic Regression, Age-Fitness Pareto Optimization, Scalable Symbolic Regression by Continuous Evolution, Symbolic Density Models, GP Transforms in Linear Regression Situations, Protein Interactions in a Computational Evolution System, Composition of Music and Financial Strategies via GP, and Evolutionary Art Using Summed Multi-Objective Ranks.

Readers will discover large-scale, real-world applications of GP to a variety of problem domains via in-depth presentations of the latest and most significant results in GP .

Keywords

Genetic Programming Genetic Programming Applications Genetic Programming Theory Symbolic regression evolution of models

Editors and affiliations

  • Rick Riolo
    • 1
  • Trent McConaghy
    • 2
  • Ekaterina Vladislavleva
    • 3
  1. 1.Center for the Study of Complex SystemsUniversity of MichiganAnn ArborUSA
  2. 2.Solido Design Automation, Inc.SaskatoonCanada
  3. 3., Dept. of Mathematics & ComputerUniversity of AntwerpAntwerpenBelgium

Bibliographic information

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Reviews

From the reviews:

“The book consists of 14 papers and an introduction. The applications it considers clearly demonstrate the maturity of GP techniques, and their ability to efficiently address difficult problem instances. … A specialized audience of experts in genetic algorithms will find state-of-the-art applications and methodologies in this book. It will also be of interest to practitioners for the large number of applications discussed, and to advanced students and researchers for the numerous opportunities for investigation and thesis topics.” (Renato De Leone, ACM Computing Reviews, July, 2011)