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  • Conference proceedings
  • © 2021

Genetic Programming

24th European Conference, EuroGP 2021, Held as Part of EvoStar 2021, Virtual Event, April 7–9, 2021, Proceedings

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 12691)

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

Conference series link(s): EuroGP: European Conference on Genetic Programming (Part of EvoStar)

Conference proceedings info: EuroGP 2021.

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Table of contents (17 papers)

  1. Front Matter

    Pages i-x
  2. Long Talks

    1. Front Matter

      Pages 1-1
    2. Progressive Insular Cooperative GP

      • Karina Brotto Rebuli, Leonardo Vanneschi
      Pages 19-35
    3. Regenerating Soft Robots Through Neural Cellular Automata

      • Kazuya Horibe, Kathryn Walker, Sebastian Risi
      Pages 36-50
    4. Inclusive Genetic Programming

      • Francesco Marchetti, Edmondo Minisci
      Pages 51-65
    5. Towards Incorporating Human Knowledge in Fuzzy Pattern Tree Evolution

      • Aidan Murphy, Gráinne Murphy, Jorge Amaral, Douglas MotaDias, Enrique Naredo, Conor Ryan
      Pages 66-81
    6. Evolutionary Neural Architecture Search Supporting Approximate Multipliers

      • Michal Pinos, Vojtech Mrazek, Lukas Sekanina
      Pages 82-97
    7. Automatic Design of Deep Neural Networks Applied to Image Segmentation Problems

      • Ricardo Lima, Aurora Pozo, Alexander Mendiburu, Roberto Santana
      Pages 98-113
    8. Evolution of Complex Combinational Logic Circuits Using Grammatical Evolution with SystemVerilog

      • Michael Kwaku Tetteh, Douglas Mota Dias, Conor Ryan
      Pages 146-161
    9. Evofficient: Reproducing a Cartesian Genetic Programming Method

      • Lorenz Wendlinger, Julian Stier, Michael Granitzer
      Pages 162-178
  3. Short Talks

    1. Front Matter

      Pages 179-179
    2. Software Anti-patterns Detection Under Uncertainty Using a Possibilistic Evolutionary Approach

      • Sofien Boutaib, Maha Elarbi, Slim Bechikh, Chih-Cheng Hung, Lamjed Ben Said
      Pages 181-197
    3. Probabilistic Grammatical Evolution

      • Jessica Mégane, Nuno Lourenço, Penousal Machado
      Pages 198-213
    4. Evolving Allocation Rules for Beam Search Heuristics in Assembly Line Balancing

      • João Pedro Gonçalves Moreira, Marcus Ritt
      Pages 214-228
    5. Incremental Evaluation in Genetic Programming

      • William B. Langdon
      Pages 229-246
    6. Mining Feature Relationships in Data

      • Andrew Lensen
      Pages 247-262
    7. Getting a Head Start on Program Synthesis with Genetic Programming

      • Jordan Wick, Erik Hemberg, Una-May O’Reilly
      Pages 263-279

Other Volumes

  1. Genetic Programming

About this book

This book constitutes the refereed proceedings of the 24th European Conference on Genetic Programming, EuroGP 2021, held as part of Evo*2021, as Virtual Event, in April 2021, co-located with the Evo*2021 events, EvoCOP, EvoMUSART, and EvoApplications. The 11 revised full papers and 6 short papers presented in this book were carefully reviewed and selected from 27 submissions. The wide range of topics in this volume reflects the current state of research in the field. The collection of papers cover interesting topics including developing new operators for variants of GP algorithms, as well as exploring GP applications to the optimisation of machine learning methods and the evolution of complex combinational logic circuits.

Editors and Affiliations

  • Queen’s University, Kingston, Canada

    Ting Hu

  • University of Coimbra, Coimbra, Portugal

    Nuno Lourenço

  • University of Trieste, Trieste, Italy

    Eric Medvet

Bibliographic Information

Buy it now

Buying options

eBook USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access