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Genetic Programming Theory and Practice XV

  • Wolfgang Banzhaf
  • Randal S. Olson
  • William Tozier
  • Rick Riolo

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

Table of contents

  1. Front Matter
    Pages i-xv
  2. Steven B. Fine, Erik Hemberg, Krzysztof Krawiec, Una-May O’Reilly
    Pages 1-16
  3. Bogdan Burlacu, Michael Affenzeller, Michael Kommenda, Gabriel Kronberger, Stephan Winkler
    Pages 17-37
  4. Emily Dolson, Wolfgang Banzhaf, Charles Ofria
    Pages 73-88
  5. Sarah Anne Troise, Thomas Helmuth
    Pages 89-104
  6. Lee Spector, William La Cava, Saul Shanabrook, Thomas Helmuth, Edward Pantridge
    Pages 105-120
  7. Randal S. Olson, Moshe Sipper, William La Cava, Sharon Tartarone, Steven Vitale, Weixuan Fu et al.
    Pages 121-134
  8. Amirhessam Tahmassebi, Amir H. Gandomi
    Pages 135-147
  9. Stjepan Picek, Erik Hemberg, Domagoj Jakobovic, Una-May O’Reilly
    Pages 149-168
  10. Zhiruo Zhao, Stuart W. Card, Kishan G. Mehrotra, Chilukuri K. Mohan
    Pages 169-184
  11. Back Matter
    Pages 185-187

About these proceedings

Introduction

These contributions, written by the foremost international researchers and practitioners of Genetic Programming (GP), explore the synergy between theoretical and empirical results on real-world problems, producing a comprehensive view of the state of the art in GP. Topics in this volume include: exploiting subprograms in genetic programming, schema frequencies in GP, Accessible AI, GP for Big Data, lexicase selection, symbolic regression techniques, co-evolution of GP and LCS, and applying ecological principles to GP. It also covers several chapters on best practices and lessons learned from hands-on experience. 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.

Keywords

Genetic Programming Genetic Programming Theory Genetic Programming Applications Symbolic Regression Symbolic Classification Evolution of Models Program Induction Artificial Evolution Machine Learning Data Analysis

Editors and affiliations

  • Wolfgang Banzhaf
    • 1
  • Randal S. Olson
    • 2
  • William Tozier
    • 3
  • Rick Riolo
    • 4
  1. 1.BEACON Center for the Study of Evolution in Action and Department of Computer ScienceMichigan State UniversityEast LansingUSA
  2. 2.Institute for Biomedical InformaticsUniversity of PennsylvaniaPhiladelphiaUSA
  3. 3.Institute for Biomedical InformaticsUniversity of PennsylvaniaPhiladelphiaUSA
  4. 4.Center for the Study of Complex SystemsUniversity of MichiganAnn ArborUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-90512-9
  • Copyright Information Springer International Publishing AG, part of Springer Nature 2018
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-90511-2
  • Online ISBN 978-3-319-90512-9
  • Series Print ISSN 1932-0167
  • Buy this book on publisher's site