Genetic Programming Theory and Practice III

  • Tina Yu
  • Rick Riolo
  • Bill Worzel

Part of the Genetic Programming book series (GPEM, volume 9)

Table of contents

  1. Front Matter
    Pages i-xv
  2. Tina Yu, Rick Riolo, Bill Worzel
    Pages 1-14
  3. H. Van Dyke Parunak
    Pages 15-32
  4. Frank D. Francone, Larry M. Deschaine, Tom Battenhouse, Jeffrey J. Warren
    Pages 49-64
  5. Jason D. Lohn, Gregory S. Hornby, Derek S. Linden
    Pages 65-78
  6. Guido Smits, Arthur Kordon, Katherine Vladislavleva, Elsa Jordaan, Mark Kotanchek
    Pages 79-92
  7. Lee Spector, Jon Klein
    Pages 109-123
  8. Riccardo Poli, William B. Langdon
    Pages 125-140
  9. R. Muhammad Atif Azad, Conor Ryan
    Pages 141-158
  10. Tuan Hao Hoang, Xuan Nguyen, R I McKay, Daryl Essam
    Pages 159-175
  11. A. Almal, W. P. Worzel, E. A. Wollesen, C. D. MacLean
    Pages 177-190
  12. Christian Jacob, Ian Burleigh
    Pages 191-206
  13. Wolfgang Banzhaf, Andre Leier
    Pages 207-221
  14. Ellery Fussell Crane, Nicholas Freitag McPhee
    Pages 223-240
  15. Arthur Kordon, Flor Castillo, Guido Smits, Mark Kotanchek
    Pages 241-258

About this book

Introduction

Genetic Programming Theory and Practice III explores the emerging interaction between theory and practice in the cutting-edge, machine learning method of Genetic Programming (GP). This contributed volume was developed from the third workshop at the University of Michigan’s Center for the Study of Complex Systems to facilitate the exchange of ideas and information related to this rapidly advancing field. The text provides a cohesive view of the issues facing both practitioners and theoreticians and examines the synergy between GP theory and application.

The foremost international researchers and practitioners in the GP arena contributed to the volume, discussing such topics as:

  • techniques to enhance GP capabilities with real-world applications and real-world application success stories from a variety of domains, including chemical and process control, informatics, and circuit design
  • visualization models to understand GP processing and
  • open challenges facing the community and potential research directions

Genetic Programming Theory and Practice III provides the most recent developments in GP theory, practice, and the integration of theory and practice. This text, the result of an extensive dialog between GP theoreticians and practitioners, is a unique and indispensable tool for both academics and industry professionals interested in the GP realm.

Keywords

Automat Variable circuit design complex system genetic programming learning machine learning programming

Editors and affiliations

  • Tina Yu
    • 1
  • Rick Riolo
    • 2
  • Bill Worzel
    • 3
  1. 1.Chevron Information Technology CompanyUSA
  2. 2.Center for the Study of Complex SystemsUniversity of MichiganUSA
  3. 3.Genetics Squared, Inc.USA

Bibliographic information

  • DOI https://doi.org/10.1007/0-387-28111-8
  • Copyright Information Springer Science+Business Media, Inc. 2006
  • Publisher Name Springer, Boston, MA
  • eBook Packages Computer Science
  • Print ISBN 978-0-387-28110-0
  • Online ISBN 978-0-387-28111-7
  • Series Print ISSN 1566-7863
  • About this book
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