Nature Inspired Cooperative Strategies for Optimization (NICSO 2010)
Juan R. González, Carlos Cruz, David Alejandro Pelta, Natalio Krasnogor, Germán Terrazas
Springer Science & Business Media, Apr 7, 2010 - Computers - 420 pages
Many aspects of Nature, Biology or even from Society have become part of the techniques and algorithms used in computer science or they have been used to enhance or hybridize several techniques through the inclusion of advanced evolution, cooperation or biologically based additions. The previous NICSO workshops were held in Granada, Spain, 2006, Acireale, Italy, 2007, and in Tenerife, Spain, 2008. As in the previous editions, NICSO 2010, held in Granada, Spain, was conceived as a forum for the latest ideas and the state of the art research related to nature inspired cooperative strategies. The contributions collected in this book cover topics including nature-inspired techniques like Genetic Algorithms, Evolutionary Algorithms, Ant and Bee Colonies, Swarm Intelligence approaches, Neural Networks, several Cooperation Models, Structures and Strategies, Agents Models, Social Interactions, as well as new algorithms based on the behaviour of fireflies or bats.
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adaptive agent Ant Colony Optimization applied approach average bee colony behaviour Berlin Heidelberg 2010 catalytic search cells chromosome cluster combination conﬁguration cooperative crossover dataset deﬁned deﬁnition e-mail efﬁcient entropy environment evaluation evolution evolutionary algorithms Evolutionary Computation evolved ﬁgure ﬁnd ﬁnding ﬁreﬂy ﬁrst ﬁtness ﬁve ﬁxed ﬂocking genes genetic algorithm Genetic Programming global heuristic IEEE imitation rule implementation inﬂuence instances iterations J.R. González LNCS MCGA MeanPSO MeanPSO MeanPSO metabolic metaheuristic method mutation Nash equilibrium NICSO nodes objective obtained optimisation optimization algorithm optimum OSGi parameters Pareto Particle Swarm Optimization performance player population problem proposed queen random Rastrigin robots Rosenbrock search space selection sensor signiﬁcant simulated solutions solve speciﬁc Springer SPSO strategy structural subsumption architecture Swarm Intelligence Table Tabu Search target test functions tion tree vector