Genetic Programming Theory and Practice XIV
Editors: Riolo, R., Worzel, B., Goldman, B., Tozier, B. (Eds.)
Free Preview- Provides chapters describing cutting-edge work on the theory and applications of genetic programming (GP)
- Offers large-scale, real-world applications of GP to a variety of problem domains
- Written by leading international experts from both academia and industry
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- About this book
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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. Chapters in this volume include:
- Similarity-based Analysis of Population Dynamics in GP Performing Symbolic Regression
- Hybrid Structural and Behavioral Diversity Methods in GP
- Multi-Population Competitive Coevolution for Anticipation of Tax Evasion
- Evolving Artificial General Intelligence for Video Game Controllers
- A Detailed Analysis of a PushGP Run
- Linear Genomes for Structured Programs
- Neutrality, Robustness, and Evolvability in GP
- Local Search in GP
- PRETSL: Distributed Probabilistic Rule Evolution for Time-Series Classification
- Relational Structure in Program Synthesis Problems with Analogical Reasoning
- An Evolutionary Algorithm for Big Data Multi-Class Classification Problems
- A Generic Framework for Building Dispersion Operators in the Semantic Space
- Assisting Asset Model Development with Evolutionary Augmentation
- Building Blocks of Machine Learning Pipelines for Initialization of a Data Science Automation Tool
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.
- Similarity-based Analysis of Population Dynamics in GP Performing Symbolic Regression
- Reviews
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“This highly technical book is meant for a very specialized audience: researchers in GP. The topics discussed offer interesting insight into how research in GP is evolving. … I strongly recommend this book for researchers in evolutionary computing and GP.” (S. V. Nagaraj, Computing Reviews, November 12, 2020)
- Table of contents (14 chapters)
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Similarity-Based Analysis of Population Dynamics in Genetic Programming Performing Symbolic Regression
Pages 1-17
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An Investigation of Hybrid Structural and Behavioral Diversity Methods in Genetic Programming
Pages 19-34
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Investigating Multi-Population Competitive Coevolution for Anticipation of Tax Evasion
Pages 35-51
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Evolving Artificial General Intelligence for Video Game Controllers
Pages 53-63
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A Detailed Analysis of a PushGP Run
Pages 65-83
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Table of contents (14 chapters)
Bibliographic Information
- Bibliographic Information
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- Book Title
- Genetic Programming Theory and Practice XIV
- Editors
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- Rick Riolo
- Bill Worzel
- Brian Goldman
- Bill Tozier
- Series Title
- Genetic and Evolutionary Computation
- Copyright
- 2018
- Publisher
- Springer International Publishing
- Copyright Holder
- Springer Nature Switzerland AG
- eBook ISBN
- 978-3-319-97088-2
- DOI
- 10.1007/978-3-319-97088-2
- Hardcover ISBN
- 978-3-319-97087-5
- Softcover ISBN
- 978-3-030-07300-8
- Series ISSN
- 1932-0167
- Edition Number
- 1
- Number of Pages
- XV, 227
- Number of Illustrations
- 52 b/w illustrations
- Topics
