Genetic Programming

20th European Conference, EuroGP 2017, Amsterdam, The Netherlands, April 19-21, 2017, Proceedings

  • James McDermott
  • Mauro Castelli
  • Lukas Sekanina
  • Evert Haasdijk
  • Pablo García-Sánchez
Conference proceedings EuroGP 2017

DOI: 10.1007/978-3-319-55696-3

Part of the Lecture Notes in Computer Science book series (LNCS, volume 10196)

Table of contents

  1. Front Matter
    Pages I-XII
    PDF

  2. Oral Presentations

    1. Front Matter
      Pages 1-1
      PDF
    2. Evolutionary Program Sketching
      Iwo Błądek, Krzysztof Krawiec
      Pages 3-18
    3. Exploring Fitness and Edit Distance of Mutated Python Programs
      Saemundur O. Haraldsson, John R. Woodward, Alexander E. I. Brownlee, David Cairns
      Pages 19-34
    4. Differentiable Genetic Programming
      Dario Izzo, Francesco Biscani, Alessio Mereta
      Pages 35-51
    5. Evolving Game State Features from Raw Pixels
      Baozhu Jia, Marc Ebner
      Pages 52-63
    6. Emergent Tangled Graph Representations for Atari Game Playing Agents
      Stephen Kelly, Malcolm I. Heywood
      Pages 64-79
    7. A General Feature Engineering Wrapper for Machine Learning Using \(\epsilon \)-Lexicase Survival
      William La Cava, Jason Moore
      Pages 80-95
    8. Visualising the Search Landscape of the Triangle Program
      William B. Langdon, Nadarajen Veerapen, Gabriela Ochoa
      Pages 96-113
    9. RANSAC-GP: Dealing with Outliers in Symbolic Regression with Genetic Programming
      Uriel López, Leonardo Trujillo, Yuliana Martinez, Pierrick Legrand, Enrique Naredo, Sara Silva
      Pages 114-130
    10. Symbolic Regression on Network Properties
      Marcus Märtens, Fernando Kuipers, Piet Van Mieghem
      Pages 131-146
    11. Evolving Time-Invariant Dispatching Rules in Job Shop Scheduling with Genetic Programming
      Yi Mei, Su Nguyen, Mengjie Zhang
      Pages 147-163
    12. Strategies for Improving the Distribution of Random Function Outputs in GSGP
      Luiz Otavio V. B. Oliveira, Felipe Casadei, Gisele L. Pappa
      Pages 164-177
    13. Synthesis of Mathematical Programming Constraints with Genetic Programming
      Tomasz P. Pawlak, Krzysztof Krawiec
      Pages 178-193
    14. Grammatical Evolution of Robust Controller Structures Using Wilson Scoring and Criticality Ranking
      Elias Reichensdörfer, Dirk Odenthal, Dirk Wollherr
      Pages 194-209
    15. Using Feature Clustering for GP-Based Feature Construction on High-Dimensional Data
      Binh Tran, Bing Xue, Mengjie Zhang
      Pages 210-226

  3. Posters

    1. Front Matter
      Pages 227-227
      PDF
    2. Geometric Semantic Crossover with an Angle-Aware Mating Scheme in Genetic Programming for Symbolic Regression
      Qi Chen, Bing Xue, Yi Mei, Mengjie Zhang
      Pages 229-245
    3. RECIPE: A Grammar-Based Framework for Automatically Evolving Classification Pipelines
      Alex G. C. de Sá, Walter José G. S. Pinto, Luiz Otavio V. B. Oliveira, Gisele L. Pappa
      Pages 246-261
    4. A Grammar Design Pattern for Arbitrary Program Synthesis Problems in Genetic Programming
      Stefan Forstenlechner, David Fagan, Miguel Nicolau, Michael O’Neill
      Pages 262-277

About these proceedings

Introduction

This book constitutes the refereed proceedings of the 20th European Conference on Genetic Programming, EuroGP 2017, held in Amsterdam, The Netherlands, in April 2017, co-located with the Evo* 2017 events, EvoCOP,  EvoMUSART, and EvoApplications.

The 14 revised full papers presented together with 8 poster papers were carefully reviewed and selected from 32 submissions. The wide range of topics in this volume reflects the current state of research in the field. Thus, we see topics  and applications including program synthesis, genetic improvement, grammatical representations, self-adaptation, multi-objective optimisation, program semantics, search landscapes, mathematical programming, games, operations research, networks, evolvable hardware, and program synthesis benchmarks.

Keywords

artificial intelligence evolutionary computation machine learning mathematical programming program synthesis benchmarks business process evolvable hardware genetic algorithms genetic improvement grammars heuristic methods linear programming multi-objective optimisation networks operations research reinforcement learning self-adaptation semantics software engineering

Editors and affiliations

  • James McDermott
    • 1
  • Mauro Castelli
    • 2
  • Lukas Sekanina
    • 3
  • Evert Haasdijk
    • 4
  • Pablo García-Sánchez
    • 5
  1. 1.University College Dublin DublinIreland
  2. 2.Universidade Nova de Lisboa LisbonPortugal
  3. 3.Brno University of Technology BrnoCzech Republic
  4. 4.Vrije Universiteit Amsterdam AmsterdamThe Netherlands
  5. 5.University of Cádiz CádizSpain

Bibliographic information

  • Copyright Information Springer International Publishing AG 2017
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-55695-6
  • Online ISBN 978-3-319-55696-3
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349