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Genetic Programming Theory and Practice XV

  • Conference proceedings
  • © 2018


  • Provides papers describing cutting-edge work on the theory and applications of genetic programming (GP)
  • Offers large-scale, real-world applications (big data) of GP to a variety of problem domains, including commercial and scientific applications as well as bioinformatics problems
  • Explores controlled semantics, lexicase and other selection methods, crossover techniques, diversity analysis and understanding of convergence tendencies

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

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Table of contents (11 papers)


About this book

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.

Editors and Affiliations

  • BEACON Center for the Study of Evolution in Action and Department of Computer Science, Michigan State University, East Lansing, USA

    Wolfgang Banzhaf

  • Institute for Biomedical Informatics, University of Pennsylvania, Philadelphia, USA

    Randal S. Olson, William Tozier

  • Center for the Study of Complex Systems, University of Michigan, Ann Arbor, USA

    Rick Riolo

Bibliographic Information

  • Book Title: Genetic Programming Theory and Practice XV

  • Editors: Wolfgang Banzhaf, Randal S. Olson, William Tozier, Rick Riolo

  • Series Title: Genetic and Evolutionary Computation

  • DOI:

  • Publisher: Springer Cham

  • eBook Packages: Computer Science, Computer Science (R0)

  • Copyright Information: Springer International Publishing AG, part of Springer Nature 2018

  • Hardcover ISBN: 978-3-319-90511-2Published: 06 July 2018

  • Softcover ISBN: 978-3-030-08031-0Published: 22 December 2018

  • eBook ISBN: 978-3-319-90512-9Published: 05 July 2018

  • Series ISSN: 1932-0167

  • Series E-ISSN: 1932-0175

  • Edition Number: 1

  • Number of Pages: XV, 187

  • Number of Illustrations: 8 b/w illustrations, 46 illustrations in colour

  • Topics: Artificial Intelligence, Computational Intelligence, Algorithm Analysis and Problem Complexity

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