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Genetic Programming

22nd European Conference, EuroGP 2019, Held as Part of EvoStar 2019, Leipzig, Germany, April 24–26, 2019, Proceedings

  • Conference proceedings
  • © 2019

Overview

Editors:
  1. Lukas Sekanina

    1. Brno University of Technology, Brno, Czech Republic

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  2. Ting Hu

    1. Memorial University, St. John's, Canada

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  3. Nuno Lourenço

    1. University of Coimbra, Coimbra, Portugal

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  4. Hendrik Richter

    1. HTWK Leipzig University of Applied Sciences, Leipzig, Germany

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  5. Pablo García-Sánchez

    1. University of Granada, Granada, Spain

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 11451)

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

Included in the following conference series:

Conference proceedings info: EuroGP 2019.

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Table of contents (18 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. Ariadne: Evolving Test Data Using Grammatical Evolution

      • Muhammad Sheraz Anjum, Conor Ryan
      Pages 3-18

    3. Quantum Program Synthesis: Swarm Algorithms and Benchmarks

      • Timothy Atkinson, Athena Karsa, John Drake, Jerry Swan
      Pages 19-34

    4. A Genetic Programming Approach to Predict Mosquitoes Abundance

      • Riccardo Gervasi, Irene Azzali, Donal Bisanzio, Andrea Mosca, Luigi Bertolotti, Mario Giacobini
      Pages 35-48

    5. Complex Network Analysis of a Genetic Programming Phenotype Network

      • Ting Hu, Marco Tomassini, Wolfgang Banzhaf
      Pages 49-63

    6. Improving Genetic Programming with Novel Exploration - Exploitation Control

      • Jonathan Kelly, Erik Hemberg, Una-May O’Reilly
      Pages 64-80

    7. Towards a Scalable EA-Based Optimization of Digital Circuits

      • Jitka Kocnova, Zdenek Vasicek
      Pages 81-97

    8. Cartesian Genetic Programming as an Optimizer of Programs Evolved with Geometric Semantic Genetic Programming

      • Ondrej Koncal, Lukas Sekanina
      Pages 98-113

    9. Can Genetic Programming Do Manifold Learning Too?

      • Andrew Lensen, Bing Xue, Mengjie Zhang
      Pages 114-130

    10. Why Is Auto-Encoding Difficult for Genetic Programming?

      • James McDermott
      Pages 131-145

    11. Solution and Fitness Evolution (SAFE): Coevolving Solutions and Their Objective Functions

      • Moshe Sipper, Jason H. Moore, Ryan J. Urbanowicz
      Pages 146-161

    12. A Model of External Memory for Navigation in Partially Observable Visual Reinforcement Learning Tasks

      • Robert J. Smith, Malcolm I. Heywood
      Pages 162-177

    13. Fault Detection and Classification for Induction Motors Using Genetic Programming

      • Yu Zhang, Ting Hu, Xiaodong Liang, Mohammad Zawad Ali, Md. Nasmus Sakib Khan Shabbir
      Pages 178-193

  3. Short Presentations

    1. Front Matter

      Pages 195-195
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    2. Fast DENSER: Efficient Deep NeuroEvolution

      • Filipe Assunção, Nuno Lourenço, Penousal Machado, Bernardete Ribeiro
      Pages 197-212

    3. A Vectorial Approach to Genetic Programming

      • Irene Azzali, Leonardo Vanneschi, Sara Silva, Illya Bakurov, Mario Giacobini
      Pages 213-227

    4. Comparison of Genetic Programming Methods on Design of Cryptographic Boolean Functions

      • Jakub Husa
      Pages 228-244

    5. Evolving AVX512 Parallel C Code Using GP

      • William B. Langdon, Ronny Lorenz
      Pages 245-261

    6. Hyper-bent Boolean Functions and Evolutionary Algorithms

      • Luca Mariot, Domagoj Jakobovic, Alberto Leporati, Stjepan Picek
      Pages 262-277
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Other volumes

  1. Genetic Programming

Keywords

About this book

This book constitutes the refereed proceedings of the 22nd European Conference on Genetic Programming, EuroGP 2019, held as part of Evo* 2019, in Leipzig, Germany, in April 2019, co-located with the Evo* events EvoCOP, EvoMUSART, and EvoApplications.

The 12 revised full papers and 6 short papers presented in this volume were carefully reviewed and selected from 36 submissions. They cover a wide range of topics and reflect the current state of research in the field. With a special focus on real-world applications in 2019, the papers are devoted to topics such as the test data design in software engineering, fault detection and classification of induction motors, digital circuit design, mosquito abundance prediction, machine learning and cryptographic function design.

 




Editors and Affiliations

  • Brno University of Technology, Brno, Czech Republic

    Lukas Sekanina

  • Memorial University, St. John's, Canada

    Ting Hu

  • University of Coimbra, Coimbra, Portugal

    Nuno Lourenço

  • HTWK Leipzig University of Applied Sciences, Leipzig, Germany

    Hendrik Richter

  • University of Granada, Granada, Spain

    Pablo García-Sánchez

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