Editors:
- Presents latest results in Nature Inspired Cooperative Strategies for Optimization
Part of the book series: Studies in Computational Intelligence (SCI, volume 129)
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Table of contents (46 chapters)
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Front Matter
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.
Editors and Affiliations
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School of Computer Sciences and Information Technology, University of Nottingham, Nottingham, UK
Natalio Krasnogor
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Department of Mathematics and Computer Science, University of Catania, Catania, Italy
Giuseppe Nicosia, Mario Pavone
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Department of Computer Science and Artificial Intelligence E.T.S. Ingenieria Informatica C/ Periodista Daniel Saucedo Aranda s/n, University of Granada, Granada, Spain
David Pelta
About the editors
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.
Bibliographic Information
Book Title: Nature Inspired Cooperative Strategies for Optimization (NICSO 2007)
Editors: Natalio Krasnogor, Giuseppe Nicosia, Mario Pavone, David Pelta
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-540-78987-1
Publisher: Springer Berlin, Heidelberg
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2008
Hardcover ISBN: 978-3-540-78986-4Published: 14 May 2008
Softcover ISBN: 978-3-642-09779-9Published: 30 November 2010
eBook ISBN: 978-3-540-78987-1Published: 03 June 2008
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: XIV, 520
Topics: Artificial Intelligence, Mathematical and Computational Engineering