Editors:
- 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)
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Front Matter
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Back Matter
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
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BEACON Center for the Study of Evolution in Action and Department of Computer Science, Michigan State University, East Lansing, USA
Wolfgang Banzhaf
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Institute for Biomedical Informatics, University of Pennsylvania, Philadelphia, USA
Randal S. Olson, William Tozier
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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: https://doi.org/10.1007/978-3-319-90512-9
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