Studies in Computational Intelligence

Nature Inspired Cooperative Strategies for Optimization (NICSO 2013)

Learning, Optimization and Interdisciplinary Applications

Editors: Terrazas, German, Otero, Fernando E. B., Masegosa, Antonio D. (Eds.)

  • Recent research on Nature Inspired Cooperative Strategies for Optimizationcrest123
  • Edited outcome of the sixth International Workshop NICSO 2013 Nature Inspired Cooperative Strategies for Optimization held September 2nd - 4th, 2013 at Canterbury, UK
  • Written by leading experts in the field
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About this book

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.

Table of contents (26 chapters)

  • Extending the ABC-Miner Bayesian Classification Algorithm

    Salama, Khalid M. (et al.)

    Pages 1-12

  • A Multiple Pheromone Ant Clustering Algorithm

    Chircop, Jan (et al.)

    Pages 13-27

  • An Island Memetic Differential Evolution Algorithm for the Feature Selection Problem

    Marinaki, Magdalene (et al.)

    Pages 29-42

  • Using a Scouting Predator-Prey Optimizer to Train Support Vector Machines with non PSD Kernels

    Silva, Arlindo (et al.)

    Pages 43-56

  • Response Surfaces with Discounted Information for Global Optima Tracking in Dynamic Environments

    Morales-Enciso, Sergio (et al.)

    Pages 57-69

Buy this book

eBook $139.00
price for USA (gross)
  • ISBN 978-3-319-01692-4
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $179.00
price for USA
  • ISBN 978-3-319-01691-7
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $179.00
price for USA
  • ISBN 978-3-319-03347-1
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Rent the ebook  
  • Rental duration: 1 or 6 month
  • low-cost access
  • online reader with highlighting and note-making option
  • can be used across all devices
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Bibliographic Information

Bibliographic Information
Book Title
Nature Inspired Cooperative Strategies for Optimization (NICSO 2013)
Book Subtitle
Learning, Optimization and Interdisciplinary Applications
Editors
  • German Terrazas
  • Fernando E. B. Otero
  • Antonio D. Masegosa
Series Title
Studies in Computational Intelligence
Series Volume
512
Copyright
2014
Publisher
Springer International Publishing
Copyright Holder
Springer International Publishing Switzerland
eBook ISBN
978-3-319-01692-4
DOI
10.1007/978-3-319-01692-4
Hardcover ISBN
978-3-319-01691-7
Softcover ISBN
978-3-319-03347-1
Series ISSN
1860-949X
Edition Number
1
Number of Pages
XIII, 355
Topics