Editors:
- Provides contributions 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 financial and insurance 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 (19 chapters)
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Front 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. In this year’s edition, the topics covered include many of the most important issues and research questions in the field, such as: opportune application domains for GP-based methods, game playing and co-evolutionary search, symbolic regression and efficient learning strategies, encodings and representations for GP, schema theorems, and new selection mechanisms.The volume includes 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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Computer Science and Engineering, John R. Koza Chair, Michigan State University, East Lansing, USA
Wolfgang Banzhaf
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BEACON Center, Michigan State University, East Lansing, USA
Erik Goodman
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Department of Computer Science and Engineering, Michigan State University, Okemos, USA
Leigh Sheneman
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Depto Ingenieria en Electronic Electrica Tecnológico Nacional de México/ IT, Tijuana, Mexico
Leonardo Trujillo
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Evolution Enterprises, Ann Arbor, USA
Bill Worzel
Bibliographic Information
Book Title: Genetic Programming Theory and Practice XVII
Editors: Wolfgang Banzhaf, Erik Goodman, Leigh Sheneman, Leonardo Trujillo, Bill Worzel
Series Title: Genetic and Evolutionary Computation
DOI: https://doi.org/10.1007/978-3-030-39958-0
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer Nature Switzerland AG 2020
Hardcover ISBN: 978-3-030-39957-3Published: 08 May 2020
Softcover ISBN: 978-3-030-39960-3Published: 08 May 2021
eBook ISBN: 978-3-030-39958-0Published: 07 May 2020
Series ISSN: 1932-0167
Series E-ISSN: 1932-0175
Edition Number: 1
Number of Pages: XXVI, 409
Number of Illustrations: 30 b/w illustrations, 112 illustrations in colour
Topics: Artificial Intelligence, Computational Intelligence, Algorithm Analysis and Problem Complexity