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Genetic Programming Theory and Practice XIII

  • Book
  • © 2016

Overview

Editors:
  1. Rick Riolo

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

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  2. W.P. Worzel

    1. Evolution Enterprises, Ann Arbor, USA

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    You can also search for this editor in PubMed   Google Scholar

  3. Mark Kotanchek

    1. Evolved Analytics, Midland, USA

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  4. Arthur Kordon

    1. Evolved Analytics LLC, Midland, USA

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  • Provides papers 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, including financial applications, genetic analysis, product selection
  • Theoretical exploration of controlled semantic, lexicase and other selection and crossover methods, and understanding convergence
  • Includes supplementary material: sn.pub/extras

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

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Table of contents (14 chapters)

  1. Front Matter

    Pages i-xx
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  2. Evolving Simple Symbolic Regression Models by Multi-Objective Genetic Programming

    • Michael Kommenda, Gabriel Kronberger, Michael Affenzeller, Stephan M. Winkler, Bogdan Burlacu
    Pages 1-19

  3. Learning Heuristics for Mining RNA Sequence-Structure Motifs

    • Achiya Elyasaf, Pavel Vaks, Nimrod Milo, Moshe Sipper, Michal Ziv-Ukelson
    Pages 21-38

  4. Kaizen Programming for Feature Construction for Classification

    • Vinícius Veloso de Melo, Wolfgang Banzhaf
    Pages 39-57

  5. GP As If You Meant It: An Exercise for Mindful Practice

    • William A. Tozier
    Pages 59-78

  6. nPool: Massively Distributed Simultaneous Evolution and Cross-Validation in EC-Star

    • Babak Hodjat, Hormoz Shahrzad
    Pages 79-90

  7. Highly Accurate Symbolic Regression with Noisy Training Data

    • Michael F. Korns
    Pages 91-115

  8. Using Genetic Programming for Data Science: Lessons Learned

    • Steven Gustafson, Ram Narasimhan, Ravi Palla, Aisha Yousuf
    Pages 117-135

  9. The Evolution of Everything (EvE) and Genetic Programming

    • W. P. Worzel
    Pages 137-149

  10. Lexicase Selection for Program Synthesis: A Diversity Analysis

    • Thomas Helmuth, Nicholas Freitag McPhee, Lee Spector
    Pages 151-167

  11. Behavioral Program Synthesis: Insights and Prospects

    • Krzysztof Krawiec, Jerry Swan, Una-May O’Reilly
    Pages 169-183

  12. Using Graph Databases to Explore the Dynamics of Genetic Programming Runs

    • Nicholas Freitag McPhee, David Donatucci, Thomas Helmuth
    Pages 185-201

  13. Predicting Product Choice with Symbolic Regression and Classification

    • Philip Truscott, Michael F. Korns
    Pages 203-217

  14. Multiclass Classification Through Multidimensional Clustering

    • Sara Silva, Luis Muñoz, Leonardo Trujillo, Vijay Ingalalli, Mauro Castelli, Leonardo Vanneschi
    Pages 219-239

  15. Prime-Time: Symbolic Regression Takes Its Place in the Real World

    • Sean Stijven, Ekaterina Vladislavleva, Arthur Kordon, Lander Willem, Mark E. Kotanchek
    Pages 241-260

  16. Back Matter

    Pages 261-262
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Keywords

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: multi-objective genetic programming, learning heuristics, Kaizen programming, Evolution of Everything (EvE), lexicase selection, behavioral program synthesis, symbolic regression with noisy training data, graph databases, and multidimensional clustering. It also covers several chapters on best practices and lesson learned from hands-on experience. Additional application areas include financial operations, genetic analysis, and predicting product choice. 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

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

    Rick Riolo

  • Evolution Enterprises, Ann Arbor, USA

    W.P. Worzel

  • Evolved Analytics, Midland, USA

    Mark Kotanchek

  • Evolved Analytics LLC, Midland, USA

    Arthur Kordon

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