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Artificial Evolution

13th International Conference, Évolution Artificielle, EA 2017, Paris, France, October 25–27, 2017, Revised Selected Papers

  • Conference proceedings
  • © 2018

Overview

Editors:
  1. Evelyne Lutton

    1. Inria, Thiverval-Grignon, France

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  2. Pierrick Legrand

    1. Inria Bordeaux, University of Bordeaux, Talence, France

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  3. Pierre Parrend

    1. ECAM Strasbourg-Europe, Schiltigheim, France

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  4. Nicolas Monmarché

    1. University of Tours, Tours, France

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  5. Marc Schoenauer

    1. Université Paris-Sud, Orsay, France

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 10764)

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

Included in the following conference series:

Conference proceedings info: EA 2017.

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Table of contents (16 papers)

  1. Front Matter

    Pages I-XVI
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  2. On the Design of a Master-Worker Adaptive Algorithm Selection Framework

    • Christopher Jankee, Sébastien Verel, Bilel Derbel, Cyril Fonlupt
    Pages 1-15

  3. Comparison of Acceptance Criteria in Randomized Local Searches

    • Alberto Franzin, Thomas Stützle
    Pages 16-29

  4. A Fitness Landscape View on the Tuning of an Asynchronous Master-Worker EA for Nuclear Reactor Design

    • Mathieu Muniglia, Sébastien Verel, Jean-Charles Le Pallec, Jean-Michel Do
    Pages 30-46

  5. Sampled Walk and Binary Fitness Landscapes Exploration

    • Sara Tari, Matthieu Basseur, Adrien Goëffon
    Pages 47-57

  6. Semantics-Based Crossover for Program Synthesis in Genetic Programming

    • Stefan Forstenlechner, David Fagan, Miguel Nicolau, Michael O’Neill
    Pages 58-71

  7. On the Use of Dynamic GP Fitness Cases in Static and Dynamic Optimisation Problems

    • Edgar Galván-López, Lucia Vázquez-Mendoza, Marc Schoenauer, Leonardo Trujillo
    Pages 72-87

  8. MEMSA: A Robust Parisian EA for Multidimensional Multiple Sequence Alignment

    • Julie D. Thompson, Renaud Vanhoutrève, Pierre Collet
    Pages 88-99

  9. Basic, Dual, Adaptive, and Directed Mutation Operators in the Fly Algorithm

    • Zainab Ali Abbood, Franck P. Vidal
    Pages 100-114

  10. A New High-Level Relay Hybrid Metaheuristic for Black-Box Optimization Problems

    • Julien Lepagnot, Lhassane Idoumghar, Mathieu Brévilliers, Maha Idrissi-Aouad
    Pages 115-128

  11. Improved Hybrid Iterative Tabu Search for QAP Using Distance Cooperation

    • Omar Abdelkafi, Lhassane Idoumghar, Julien Lepagnot
    Pages 129-143

  12. H-ACO: A Heterogeneous Ant Colony Optimisation Approach with Application to the Travelling Salesman Problem

    • Ahamed Fayeez Tuani, Edward Keedwell, Matthew Collett
    Pages 144-161

  13. Evolutionary Learning of Fire Fighting Strategies

    • Martin Kretschmer, Elmar Langetepe
    Pages 162-175

  14. Evolutionary Optimization of Tone Mapped Image Quality Index

    • Xihe Gao, Jeremy Porter, Stephen Brooks, Dirk V. Arnold
    Pages 176-188

  15. LIDeOGraM: An Interactive Evolutionary Modelling Tool

    • Thomas Chabin, Marc Barnabé, Nadia Boukhelifa, Fernanda Fonseca, Alberto Tonda, Hélène Velly et al.
    Pages 189-201

  16. Automatic Configuration of GCC Using Irace

    • Leslie Pérez Cáceres, Federico Pagnozzi, Alberto Franzin, Thomas Stützle
    Pages 202-216

  17. Offline Learning for Selection Hyper-heuristics with Elman Networks

    • William B. Yates, Edward C. Keedwell
    Pages 217-230

  18. Back Matter

    Pages 231-231
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  1. Artificial Evolution

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About this book

This book constitutes the thoroughly refereed post-conference proceedings of the 13th International Conference on Artificial Evolution, EA 2017, held in Paris, France, in October 2017.

 The 16 revised papers were carefully reviewed and selected from 33 submissions. The papers cover a wide range of topics in the field of artificial evolution, such as evolutionary computation, evolutionary optimization, co-evolution, artificial life, population dynamics, theory, algorithmics and modeling, implementations, application of evolutionary paradigms to the real world (industry, biosciences, ...), other biologically-inspired paradigms (swarm, artificial ants, artificial immune systems, cultural algorithms...), memetic algorithms, multi-objective optimisation, constraint handling, parallel algorithms,, dynamic optimization, machine learning and hybridization with other soft computing techniques.




Editors and Affiliations

  • Inria, Thiverval-Grignon, France

    Evelyne Lutton

  • Inria Bordeaux, University of Bordeaux, Talence, France

    Pierrick Legrand

  • ECAM Strasbourg-Europe, Schiltigheim, France

    Pierre Parrend

  • University of Tours, Tours, France

    Nicolas Monmarché

  • Université Paris-Sud, Orsay, France

    Marc Schoenauer

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