Nature Inspired Cooperative Strategies for Optimization (NICSO 2007)

  • Natalio Krasnogor
  • Giuseppe Nicosia
  • Mario Pavone
  • David Pelta

Part of the Studies in Computational Intelligence book series (SCI, volume 129)

Table of contents

  1. Front Matter
    Pages i-xiv
  2. Efrén Mezura-Montes, Lucía Muñoz-Dávila, Carlos A. Coello Coello
    Pages 1-14
  3. Brian M. Cerny, Chi Zhou, Weimin Xiao, Peter C. Nelson
    Pages 15-26
  4. Jesse St. Charles, Thomas E. Potok, Robert Patton, Xiaohui Cui
    Pages 27-37
  5. Slavisa Sarafijanovic, Jean-Yves Le Boudec
    Pages 39-51
  6. Alberto Castellini, Vincenzo Manca, Luca Marchetti
    Pages 53-62
  7. Agostino Forestiero, Carlo Mastroianni, Giandomenico Spezzano
    Pages 63-72
  8. A. M. Mora, J. J. Merelo, J. L. J. Laredo, P. A. Castillo, P. G. Sánchez, J. P. Sevilla et al.
    Pages 73-84
  9. J. M. Cadenas, M. C. Garrido, E. Muñoz
    Pages 95-104
  10. Rodica Ioana Lung, D. Dumitrescu
    Pages 105-114
  11. Antonio D. Masegosa, Alejandro Sancho Royo, David Pelta
    Pages 125-137
  12. Yannis Marinakis, Magdalene Marinaki, Georgios Dounias
    Pages 139-148
  13. Giovanni Busonera, Stefano Carucci, Danilo Pani, Luigi Raffo
    Pages 149-158
  14. Fatemeh Vafaee, Peter C. Nelson, Chi Zhou, Weimin Xiao
    Pages 159-168
  15. Malek Aichour, Evelyne Lutton
    Pages 169-178
  16. Matti Pöllä, Timo Honkela, Xiao-Zhi Gao
    Pages 179-188
  17. Juan Pedro Castro Gutiérrez, Belén Melián Batista, José A. Moreno Pérez, J. Marcos Moreno Vega, Jonatan Ramos Bonilla
    Pages 189-198
  18. Gregory Gutin, Daniel Karapetyan, Natalio Krasnogor
    Pages 199-210

About this book


Biological and natural processes have been a continuous source of inspiration for the sciences and engineering. For instance, the work of Wiener in cybernetics was influenced by feedback control processes observable in biological systems; McCulloch and Pitts description of the artificial neuron was instigated by biological observations of neural mechanisms; the idea of survival of the fittest inspired the field of evolutionary algorithms and similarly, artificial immune systems, ant colony optimisation, automated self-assembling programming, membrane computing, etc. also have their roots in natural phenomena.

The second International Workshop on Nature Inspired Cooperative Strategies for Optimization (NICSO), was held in Acireale, Italy, during November 8-10, 2007. The aim for NICSO 2007 was to provide a forum were the latest ideas and state of the art research related to cooperative strategies for problem solving arising from Nature could be discussed. The contributions collected in this book were strictly peer reviewed by at least three members of the international programme committee, to whom we are indebted for their support and assistance. The topics covered by the contributions include several well established nature inspired techniques like Genetic Algorithms, Ant Colonies, Artificial Immune Systems, Evolutionary Robotics, Evolvable Systems, Membrane Computing, Quantum Computing, Software Self Assembly, Swarm Intelligence, etc.


Computational Intelligence Evolution Nature Inspired Cooperative Strategies Optimization architecture combinatorial optimization evolutionary algorithm genetic algorithms heuristics intelligence learning metaheuristic natural language neural network robot

Editors and affiliations

  • Natalio Krasnogor
    • 1
  • Giuseppe Nicosia
    • 2
  • Mario Pavone
    • 2
  • David Pelta
    • 3
  1. 1.School of Computer Sciences and Information TechnologyUniversity of NottinghamNottinghamUK
  2. 2.Department of Mathematics and Computer ScienceUniversity of CataniaCataniaItaly
  3. 3.Department of Computer Science and Artificial Intelligence E.T.S. Ingenieria Informatica C/ Periodista Daniel Saucedo Aranda s/nUniversity of GranadaGranadaSpain

Bibliographic information

  • DOI
  • Copyright Information Springer Berlin Heidelberg 2008
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering
  • Print ISBN 978-3-540-78986-4
  • Online ISBN 978-3-540-78987-1
  • Series Print ISSN 1860-949X
  • About this book