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Genetic Programming Theory and Practice XIX

  • Book
  • © 2023

Overview

Editors:
  1. Leonardo Trujillo

    1. Engineering Sciences Graduate Program, Tecnológico Nacional de México/Instituto Tecnológico de Tijuana, Tijuana, Mexico

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  2. Stephan M. Winkler

    1. Heuristic and Evolutionary Algorithms Laboratory, University of Applied Sciences Upper Austria, Wels, Austria

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  3. Sara Silva

    1. Department of Informatics, Faculty of Sciences, University of Lisbon, Lisbon, Portugal

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  4. Wolfgang Banzhaf

    1. Department of Computer Science and Engineering, Michigan State University, East Lansing, USA

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  • Provides a unique combination of theoretical contributions and state-of-the-art real-world problem
  • Explores the intersection of genetic programming and evolutionary computation in general
  • Discusses recent results in methodological improvements to genetic programming

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

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Table of contents (11 chapters)

  1. Front Matter

    Pages i-xiv
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  2. Symbolic Regression in Materials Science: Discovering Interatomic Potentials from Data

    • Bogdan Burlacu, Michael Kommenda, Gabriel Kronberger, Stephan M. Winkler, Michael Affenzeller
    Pages 1-30

  3. Correlation Versus RMSE Loss Functions in Symbolic Regression Tasks

    • Nathan Haut, Wolfgang Banzhaf, Bill Punch
    Pages 31-55

  4. GUI-Based, Efficient Genetic Programming and AI Planning for Unity3D

    • Robert Gold, Andrew Haydn Grant, Erik Hemberg, Chathika Gunaratne, Una-May O’Reilly
    Pages 57-79

  5. Genetic Programming for Interpretable and Explainable Machine Learning

    • Ting Hu
    Pages 81-90

  6. Biological Strategies ParetoGP Enables Analysis of Wide and Ill-Conditioned Data from Nonlinear Systems

    • Mark Kotanchek, Theresa Kotanchek, Kelvin Kotanchek
    Pages 91-116

  7. GP-Based Generative Adversarial Models

    • Penousal Machado, Francisco Baeta, Tiago Martins, João Correia
    Pages 117-140

  8. Modeling Hierarchical Architectures with Genetic Programming and Neuroscience Knowledge for Image Classification Through Inferential Knowledge

    • Gustavo Olague, Matthieu Olague, Gerardo Ibarra-Vazquez, Isnardo Reducindo, Aaron Barrera, Axel Martinez et al.
    Pages 141-166

  9. Life as a Cyber-Bio-Physical System

    • Susan Stepney
    Pages 167-200

  10. STREAMLINE: A Simple, Transparent, End-To-End Automated Machine Learning Pipeline Facilitating Data Analysis and Algorithm Comparison

    • Ryan Urbanowicz, Robert Zhang, Yuhan Cui, Pranshu Suri
    Pages 201-231

  11. Evolving Complexity is Hard

    • Alden H. Wright, Cheyenne L. Laue
    Pages 233-253

  12. ESSAY: Computers Are Useless ... They Only Give Us Answers

    • Bill Worzel
    Pages 255-260

  13. Back Matter

    Pages 261-262
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Keywords

About this book

This book brings together some of the most impactful researchers in the field of Genetic Programming (GP), each one working on unique and interesting intersections of theoretical development and practical applications of this evolutionary-based machine learning paradigm. Topics of particular interest for this year´s book include powerful modeling techniques through GP-based symbolic regression, novel selection mechanisms that help guide the evolutionary process, modular approaches to GP, and applications in cybersecurity, biomedicine and program synthesis, as well as papers by practitioner of GP that focus on usability and real-world results. In summary, readers will get a glimpse of the current state of the art in GP research.

Editors and Affiliations

  • Engineering Sciences Graduate Program, Tecnológico Nacional de México/Instituto Tecnológico de Tijuana, Tijuana, Mexico

    Leonardo Trujillo

  • Heuristic and Evolutionary Algorithms Laboratory, University of Applied Sciences Upper Austria, Wels, Austria

    Stephan M. Winkler

  • Department of Informatics, Faculty of Sciences, University of Lisbon, Lisbon, Portugal

    Sara Silva

  • Department of Computer Science and Engineering, Michigan State University, East Lansing, USA

    Wolfgang Banzhaf

Bibliographic Information

  • Book Title: Genetic Programming Theory and Practice XIX

  • Editors: Leonardo Trujillo, Stephan M. Winkler, Sara Silva, Wolfgang Banzhaf

  • Series Title: Genetic and Evolutionary Computation

  • DOI: https://doi.org/10.1007/978-981-19-8460-0

  • Publisher: Springer Singapore

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

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023

  • Hardcover ISBN: 978-981-19-8459-4Published: 12 March 2023

  • Softcover ISBN: 978-981-19-8462-4Published: 13 March 2024

  • eBook ISBN: 978-981-19-8460-0Published: 11 March 2023

  • Series ISSN: 1932-0167

  • Series E-ISSN: 1932-0175

  • Edition Number: 1

  • Number of Pages: XIV, 262

  • Number of Illustrations: 11 b/w illustrations, 93 illustrations in colour

  • Topics: Theory of Computation, Biomedical Engineering and Bioengineering, Algorithms

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