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Genetic Programming Theory and Practice VII

  • Rick Riolo
  • Una-May O'Reilly
  • Trent McConaghy

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

Table of contents

  1. Front Matter
    Pages 1-13
  2. Una-May O’Reilly, Trent McConaghy, Rick Riolo
    Pages 1-18
  3. John Doucette, Peter Lichodzijewski, Malcolm Heywood
    Pages 37-54
  4. Mark E. Kotanchek, Ekaterina Y. Vladislavleva, Guido F. Smits
    Pages 55-72
  5. Michael Schmidt, Hod Lipson
    Pages 73-85
  6. Garnett Wilson, Wolfgang Banzhaf
    Pages 119-134
  7. Luca Citi, Riccardo Poli, Caterina Cinel
    Pages 135-157
  8. Shinichi Shirakawa, Tomoharu Nagao
    Pages 177-194
  9. Back Matter
    Pages 1-3

About this book

Introduction

Genetic programming has emerged as an important computational methodology for solving complex problems in a diversity of disciplines. In an effort to foster collaborations and facilitate the exchange of ideas and information related to the rapidly advancing field of Genetic Programming, the annual Genetic Programming Theory and Practice Workshop was organized by the University of Michigan’s Center for the Study of Complex Systems to provide a forum for both those who develop computational theory and those that practice the art of computation.

Genetic Programming Theory and Practice VII presents the results of this workshop, contributed by the foremost international researchers and practitioners in the GP arena. Contributions examine the similarities and differences between theoretical and empirical results on real-world problems, and explore the synergy between theory and practice, producing a comprehensive view of the state of the art in GP application. Application areas include chemical process control, circuit design, financial data mining and bio-informatics, to name a few.

About this book:

  • Discusses the hurdles encountered when solving large-scale, cutting-edge applications
  • Provides in-depth presentations of the latest and most significant applications of GP and the most recent theoretical results with direct applicability to state-of-the-art problems
  • Contributed by GP theorists from major universities and active practitioners from industry examining how GP theory informs practice and how GP practice impacts GP theory

Genetic Programming Theory and Practice VII is suitable for researchers, practitioners and students of Genetic Programming, including industry technical staffs, technical consultants and business entrepreneurs.

Keywords

Artificial Intelligence Automatic Programming Evolution of Models Evolutionary Computation Genetic Algorithms Problem Solving Search Algorithms Symbolic Regression algorithms ants currentjm

Editors and affiliations

  • Rick Riolo
    • 1
  • Una-May O'Reilly
    • 2
  • Trent McConaghy
    • 3
  1. 1.Center for the Study of Complex SystemsUniversity of MichiganAnn ArborU.S.A.
  2. 2.Computer Science &Massachusetts Institute of TechnologyCambridgeU.S.A.
  3. 3.Solido Design Automation, Inc.SaskatoonCanada

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4419-1626-6
  • Copyright Information Springer Science+Business Media, LLC 2010
  • Publisher Name Springer, Boston, MA
  • eBook Packages Computer Science
  • Print ISBN 978-1-4419-1625-9
  • Online ISBN 978-1-4419-1626-6
  • Series Print ISSN 1932-0167
  • Buy this book on publisher's site
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