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Genetic Programming

14th European Conference, EuroGP 2011, Torino, Italy, April 27-29, 2011, Proceedings

  • Conference proceedings
  • © 2011

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Editors:
  1. Sara Silva

    1. INESC-ID Lisboa, Lisboa, Portugal

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  2. James A. Foster

    1. Department of Biological Sciences, University of Idaho, Moscow, USA

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  3. Miguel Nicolau

    1. University College Dublin, UCD CASL, Belfield, Ireland

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  4. Penousal Machado

    1. Faculty of Sciences and Technology, Department of Informatics Engineering, University of Coimbra, Coimbra, Portugal

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  5. Mario Giacobini

    1. Department of Animal Production Epidemiology and Ecology, University of Torino, Grugliasco (TO), Italy

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 6621)

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

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Conference proceedings info: EuroGP 2011.

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About this book

This book constitutes the refereed proceedings of the 14th European Conference on Genetic Programming, EuroGP 2011, held in Torino, Italy, in April 2011 co-located with the Evo* 2011 events.
This 20 revised full papers presented together with 9 poster papers were carefully reviewed and selected from 59 submissions. The wide range of topics in this volume reflect the current state of research in the field, including representations, theory, novel operators and techniques, self organization, and applications.

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Table of contents (29 papers)

  1. Front Matter

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  2. Oral Presentations

    1. A Sniffer Technique for an Efficient Deduction of Model Dynamical Equations Using Genetic Programming

      • Dilip P. Ahalpara, Abhijit Sen
      Pages 1-12

    2. Robustness, Evolvability, and Accessibility in Linear Genetic Programming

      • Ting Hu, Joshua L. Payne, Wolfgang Banzhaf, Jason H. Moore
      Pages 13-24

    3. A Quantitative Study of Learning and Generalization in Genetic Programming

      • Mauro Castelli, Luca Manzoni, Sara Silva, Leonardo Vanneschi
      Pages 25-36

    4. GP-Based Electricity Price Forecasting

      • Alberto Bartoli, Giorgio Davanzo, Andrea De Lorenzo, Eric Medvet
      Pages 37-48

    5. Novel Loop Structures and the Evolution of Mathematical Algorithms

      • Mingxu Wan, Thomas Weise, Ke Tang
      Pages 49-60

    6. Maximum Margin Decision Surfaces for Increased Generalisation in Evolutionary Decision Tree Learning

      • Alexandros Agapitos, Michael O’Neill, Anthony Brabazon, Theodoros Theodoridis
      Pages 61-72

    7. Evolving Cell Array Configurations Using CGP

      • Paul Bremner, Mohammad Samie, Gabriel Dragffy, Anthony. G. Pipe, Yang Liu
      Pages 73-84

    8. Designing Pheromone Update Strategies with Strongly Typed Genetic Programming

      • Jorge Tavares, Francisco B. Pereira
      Pages 85-96

    9. Random Lines: A Novel Population Set-Based Evolutionary Global Optimization Algorithm

      • İsmet Şahin
      Pages 97-107

    10. A Peer-to-Peer Approach to Genetic Programming

      • Juan Luis Jiménez Laredo, Daniel Lombraña González, Francisco Fernández de Vega, Maribel García Arenas, Juan Julián Merelo Guervós
      Pages 108-117

    11. Performance Models for Evolutionary Program Induction Algorithms Based on Problem Difficulty Indicators

      • Mario Graff, Riccardo Poli
      Pages 118-129

    12. Examining Mutation Landscapes in Grammar Based Genetic Programming

      • Eoin Murphy, Michael O’Neill, Anthony Brabazon
      Pages 130-141

    13. ReNCoDe: A Regulatory Network Computational Device

      • Rui L. Lopes, Ernesto Costa
      Pages 142-153

    14. Statistical Distribution of Generation-to-Success in GP: Application to Model Accumulated Success Probability

      • David F. Barrero, Bonifacio Castaño, María D. R-Moreno, David Camacho
      Pages 154-165

    15. Learnable Embeddings of Program Spaces

      • Krzysztof Krawiec
      Pages 166-177

    16. Parallel Linear Genetic Programming

      • Carlton Downey, Mengjie Zhang
      Pages 178-189

    17. How Far Is It from Here to There? A Distance That Is Coherent with GP Operators

      • James McDermott, Una-May O’Reilly, Leonardo Vanneschi, Kalyan Veeramachaneni
      Pages 190-202

    18. Evolution of a Brain-Computer Interface Mouse via Genetic Programming

      • Riccardo Poli, Mathew Salvaris, Caterina Cinel
      Pages 203-214

    19. Operator Self-adaptation in Genetic Programming

      • Min Hyeok Kim, Robert Ian (Bob) McKay, Nguyen Xuan Hoai, Kangil Kim
      Pages 215-226
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Other volumes

  1. Genetic Programming

Editors and Affiliations

  • INESC-ID Lisboa, Lisboa, Portugal

    Sara Silva

  • Department of Biological Sciences, University of Idaho, Moscow, USA

    James A. Foster

  • University College Dublin, UCD CASL, Belfield, Ireland

    Miguel Nicolau

  • Faculty of Sciences and Technology, Department of Informatics Engineering, University of Coimbra, Coimbra, Portugal

    Penousal Machado

  • Department of Animal Production Epidemiology and Ecology, University of Torino, Grugliasco (TO), Italy

    Mario Giacobini

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