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Genetic Programming

21st European Conference, EuroGP 2018, Parma, Italy, April 4-6, 2018, Proceedings

  • Conference proceedings
  • © 2018

Overview

Editors:
  1. Mauro Castelli

    1. Universidade Nova de Lisboa, Lisbon, Portugal

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  2. Lukas Sekanina

    1. Brno University of Technology, Brno, Czech Republic

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  3. Mengjie Zhang

    1. Victoria University of Wellington, Wellington, New Zealand

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  4. Stefano Cagnoni

    1. University of Parma, Parma, Italy

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  5. Pablo García-Sánchez

    1. University of Cádiz, Cádiz, Spain

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 10781)

Part of the book sub series: Theoretical Computer Science and General Issues (LNTCS)

Included in the following conference series:

Conference proceedings info: EuroGP 2018.

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Table of contents (19 papers)

  1. Front Matter

    Pages I-XII
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  2. Long Presentations

    1. Front Matter

      Pages 1-1
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    2. Using GP Is NEAT: Evolving Compositional Pattern Production Functions

      • Filipe Assunção, Nuno Lourenço, Penousal Machado, Bernardete Ribeiro
      Pages 3-18

    3. Evolving the Topology of Large Scale Deep Neural Networks

      • Filipe Assunção, Nuno Lourenço, Penousal Machado, Bernardete Ribeiro
      Pages 19-34

    4. Evolving Graphs by Graph Programming

      • Timothy Atkinson, Detlef Plump, Susan Stepney
      Pages 35-51

    5. Pruning Techniques for Mixed Ensembles of Genetic Programming Models

      • Mauro Castelli, Ivo Gonçalves, Luca Manzoni, Leonardo Vanneschi
      Pages 52-67

    6. Analyzing Feature Importance for Metabolomics Using Genetic Programming

      • Ting Hu, Karoliina Oksanen, Weidong Zhang, Edward Randell, Andrew Furey, Guangju Zhai
      Pages 68-83

    7. Generating Redundant Features with Unsupervised Multi-tree Genetic Programming

      • Andrew Lensen, Bing Xue, Mengjie Zhang
      Pages 84-100

    8. On the Automatic Design of a Representation for Grammar-Based Genetic Programming

      • Eric Medvet, Alberto Bartoli
      Pages 101-117

    9. Multi-level Grammar Genetic Programming for Scheduling in Heterogeneous Networks

      • Takfarinas Saber, David Fagan, David Lynch, Stepan Kucera, Holger Claussen, Michael O’Neill
      Pages 118-134

    10. Scaling Tangled Program Graphs to Visual Reinforcement Learning in ViZDoom

      • Robert J. Smith, Malcolm I. Heywood
      Pages 135-150

    11. Towards in Vivo Genetic Programming: Evolving Boolean Networks to Determine Cell States

      • Nadia S. Taou, Michael A. Lones
      Pages 151-165

    12. A Multiple Expression Alignment Framework for Genetic Programming

      • Leonardo Vanneschi, Kristen Scott, Mauro Castelli
      Pages 166-183

  3. Short Presentations

    1. Front Matter

      Pages 185-185
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    2. Multi-objective Evolution of Ultra-Fast General-Purpose Hash Functions

      • David Grochol, Lukas Sekanina
      Pages 187-202

    3. A Comparative Study on Crossover in Cartesian Genetic Programming

      • Jakub Husa, Roman Kalkreuth
      Pages 203-219

    4. Evolving Better RNAfold Structure Prediction

      • William B. Langdon, Justyna Petke, Ronny Lorenz
      Pages 220-236

    5. Geometric Crossover in Syntactic Space

      • João Macedo, Carlos M. Fonseca, Ernesto Costa
      Pages 237-252

    6. Investigating a Machine Breakdown Genetic Programming Approach for Dynamic Job Shop Scheduling

      • John Park, Yi Mei, Su Nguyen, Gang Chen, Mengjie Zhang
      Pages 253-270

    7. Structurally Layered Representation Learning: Towards Deep Learning Through Genetic Programming

      • Lino Rodriguez-Coayahuitl, Alicia Morales-Reyes, Hugo Jair Escalante
      Pages 271-288
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Other volumes

  1. Genetic Programming

Keywords

About this book

This book constitutes the refereed proceedings of the 21st European Conference on Genetic Programming, EuroGP 2018, held in Parma, Italy, in April 2018, co-located with the Evo* 2018 events, EvoCOP, EvoMUSART, and EvoApplications.

The 11 revised full papers presented together with 8 poster papers were carefully reviewed and selected from 36 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 analysis of feature importance for metabolomics, semantic methods, evolution of boolean networks, generation of redundant features, ensembles of GP models, automatic design of grammatical representations, GP and neuroevolution, visual reinforcement learning, evolution of deep neural networks, evolution of graphs, and scheduling in heterogeneous networks.

Editors and Affiliations

  • Universidade Nova de Lisboa, Lisbon, Portugal

    Mauro Castelli

  • Brno University of Technology, Brno, Czech Republic

    Lukas Sekanina

  • Victoria University of Wellington, Wellington, New Zealand

    Mengjie Zhang

  • University of Parma, Parma, Italy

    Stefano Cagnoni

  • University of Cádiz, Cádiz, Spain

    Pablo García-Sánchez

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