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» Entropy-Driven Parameter Control for Evolutionary Algorithms
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GECCO
2005
Springer
220views Optimization» more  GECCO 2005»
14 years 1 months ago
Scale invariant pareto optimality: a meta--formalism for characterizing and modeling cooperativity in evolutionary systems
This article describes a mathematical framework for characterizing cooperativity in complex systems subject to evolutionary pressures. This framework uses three foundational compo...
Mark Fleischer
CONSTRAINTS
2002
143views more  CONSTRAINTS 2002»
13 years 7 months ago
A Constraint-Based Robotic Soccer Team
It is a challenging task for a team of multiple fast-moving robots to cooperate with each other and to compete with another team in a dynamic, real-time environment. For a robot te...
Yu Zhang, Alan K. Mackworth
DEXA
2008
Springer
123views Database» more  DEXA 2008»
13 years 9 months ago
Evolutionary Clustering in Description Logics: Controlling Concept Formation and Drift in Ontologies
Abstract. We present a method based on clustering techniques to detect concept drift or novelty in a knowledge base expressed in Description Logics. The method exploits an effectiv...
Nicola Fanizzi, Claudia d'Amato, Floriana Esposito
PRL
2002
128views more  PRL 2002»
13 years 7 months ago
Dynamic flies: a new pattern recognition tool applied to stereo sequence processing
The "fly algorithm" is a fast artificial evolution-based technique devised for the exploration of parameter space in pattern recognition applications. In the application...
Jean Louchet, Maud Guyon, Marie-Jeanne Lesot, Amin...
GECCO
2008
Springer
143views Optimization» more  GECCO 2008»
13 years 8 months ago
Application domain study of evolutionary algorithms in optimization problems
This paper deals with the problem of comparing and testing evolutionary algorithms, that is, the benchmarking problem, from an analysis point of view. A practical study of the app...
Pilar Caamaño, Francisco Bellas, José...