Nature Inspired Cooperative Strategies for Optimization (NICSO 2013)

Learning, Optimization and Interdisciplinary Applications

  • German Terrazas
  • Fernando E. B. Otero
  • Antonio D. Masegosa

Part of the Studies in Computational Intelligence book series (SCI, volume 512)

Table of contents

  1. Front Matter
    Pages 1-12
  2. Khalid M. Salama, Alex A. Freitas
    Pages 1-12
  3. Jan Chircop, Christopher D. Buckingham
    Pages 13-27
  4. Harish Sharma, Pragati Shrivastava, Jagdish Chand Bansal, Ritu Tiwari
    Pages 71-84
  5. Jenny Fajardo Calderín, Antonio D. Masegosa, Alejandro Rosete Suárez, David A. Pelta
    Pages 85-97
  6. E. Osaba, E. Onieva, R. Carballedo, F. Diaz, A. Perallos
    Pages 113-124
  7. Hélio Freire, P. B. de Moura Oliveira, E. J. Solteiro Pires, Maximino Bessa
    Pages 125-139
  8. Vincenzo Cutello, Angelo G. De Michele, Mario Pavone
    Pages 141-152
  9. J. Dafni Rose, Divya D. Dev, C. R. Rene Robin
    Pages 153-166
  10. Ana Paula Silva, Arlindo Silva, Irene Rodrigues
    Pages 167-178
  11. Malika Bessedik, Asma Daoudi, Karima Benatchba
    Pages 179-190
  12. John A. Bullinaria, Khulood AlYahya
    Pages 191-201
  13. Eddy Mesa, Juan David Velásquez, Gloria Patricia Jaramillo
    Pages 203-215
  14. Jesse van den Kieboom, Soha Pouya, Auke Jan Ijspeert
    Pages 231-244

About this book

Introduction

Biological and other natural processes have always been a source of inspiration for computer science and information technology. Many emerging problem solving techniques integrate advanced evolution and cooperation strategies, encompassing a range of spatio-temporal scales for visionary conceptualization of evolutionary computation.

This book is a collection of research works presented in the VI International Workshop on Nature Inspired Cooperative Strategies for Optimization (NICSO) held in Canterbury, UK. Previous editions of NICSO were held in Granada, Spain (2006 & 2010), Acireale, Italy (2007), Tenerife, Spain (2008), and Cluj-Napoca, Romania (2011). NICSO 2013 and this book provides a place where state-of-the-art research, latest ideas and emerging areas of nature inspired cooperative strategies for problem solving are vigorously discussed and exchanged among the scientific community. The breadth and variety of articles in this book report on nature inspired methods and applications such as Swarm Intelligence, Hyper-heuristics, Evolutionary Algorithms, Cellular Automata, Artificial Bee Colony, Dynamic Optimization, Support Vector Machines, Multi-Agent Systems, Ant Clustering, Evolutionary Design Optimisation, Game Theory and other several Cooperation Models.

Keywords

Computational Intelligence Nature Inspired Cooperative Strategies for Optimization

Editors and affiliations

  • German Terrazas
    • 1
  • Fernando E. B. Otero
    • 2
  • Antonio D. Masegosa
    • 3
  1. 1.School of Computer ScienceUniversity of NottinghamNottinghamUnited Kingdom
  2. 2.School of ComputingUniversity of KentCanterburyUnited Kingdom
  3. 3.Center for Research on ICTUniversity of GranadaGranadaSpain

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-01692-4
  • Copyright Information Springer International Publishing Switzerland 2014
  • Publisher Name Springer, Cham
  • eBook Packages Engineering
  • Print ISBN 978-3-319-01691-7
  • Online ISBN 978-3-319-01692-4
  • Series Print ISSN 1860-949X
  • Series Online ISSN 1860-9503
  • About this book
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