Genetic Programming Theory and Practice XIII

  • Rick Riolo
  • W.P.  Worzel
  • Mark Kotanchek
  • Arthur Kordon

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

Table of contents

  1. Front Matter
    Pages i-xx
  2. Michael Kommenda, Gabriel Kronberger, Michael Affenzeller, Stephan M. Winkler, Bogdan Burlacu
    Pages 1-19
  3. Achiya Elyasaf, Pavel Vaks, Nimrod Milo, Moshe Sipper, Michal Ziv-Ukelson
    Pages 21-38
  4. Vinícius Veloso de Melo, Wolfgang Banzhaf
    Pages 39-57
  5. Steven Gustafson, Ram Narasimhan, Ravi Palla, Aisha Yousuf
    Pages 117-135
  6. Thomas Helmuth, Nicholas Freitag McPhee, Lee Spector
    Pages 151-167
  7. Krzysztof Krawiec, Jerry Swan, Una-May O’Reilly
    Pages 169-183
  8. Nicholas Freitag McPhee, David Donatucci, Thomas Helmuth
    Pages 185-201
  9. Philip Truscott, Michael F. Korns
    Pages 203-217
  10. Sara Silva, Luis Muñoz, Leonardo Trujillo, Vijay Ingalalli, Mauro Castelli, Leonardo Vanneschi
    Pages 219-239
  11. Sean Stijven, Ekaterina Vladislavleva, Arthur Kordon, Lander Willem, Mark E. Kotanchek
    Pages 241-260
  12. Back Matter
    Pages 261-262

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.


Feature generation Genetic programming Symbolic regression Machine learning Evolutionary algorithms Semantic programming Geometric programming Big data Cloud computing Data science Hyper heuristics Multi-objective optimization Lexicase selection Singularity

Editors and affiliations

  • Rick Riolo
    • 1
  • W.P.  Worzel
    • 2
  • Mark Kotanchek
    • 3
  • Arthur Kordon
    • 4
  1. 1.Center for the Study of Complex SystemsUniversity of MichiganAnn ArborUSA
  2. 2.Evolution EnterprisesAnn ArborUSA
  3. 3.Evolved AnalyticsMidlandUSA
  4. 4.Evolved Analytics LLCMidlandUSA

Bibliographic information