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GECCO
2005
Springer
110views Optimization» more  GECCO 2005»
14 years 1 months ago
Understanding cooperative co-evolutionary dynamics via simple fitness landscapes
Cooperative co-evolution is often used to solve difficult optimization problems by means of problem decomposition. Its performance for such tasks can vary widely from good to disa...
Elena Popovici, Kenneth A. De Jong
GECCO
2006
Springer
158views Optimization» more  GECCO 2006»
13 years 11 months ago
The effects of interaction frequency on the optimization performance of cooperative coevolution
Cooperative coevolution is often used to solve difficult optimization problems by means of problem decomposition. Its performance on this task is influenced by many design decisio...
Elena Popovici, Kenneth A. De Jong
AI
2004
Springer
14 years 27 days ago
On Customizing Evolutionary Learning of Agent Behavior
The fitness function of an evolutionary algorithm is one of the few possible spots where application knowledge can be made available to the algorithm. But the representation and u...
Jörg Denzinger, Alvin Schur
EVOW
2008
Springer
13 years 9 months ago
An Evolutionary Game-Theoretical Approach to Particle Swarm Optimisation
Abstract. This work merges ideas from two very different areas: Particle Swarm Optimisation and Evolutionary Game Theory. In particular, we are looking to integrate strategies from...
Cecilia Di Chio, Paolo Di Chio, Mario Giacobini
JMLR
2008
92views more  JMLR 2008»
13 years 7 months ago
Theoretical Advantages of Lenient Learners: An Evolutionary Game Theoretic Perspective
This paper presents the dynamics of multiple learning agents from an evolutionary game theoretic perspective. We provide replicator dynamics models for cooperative coevolutionary ...
Liviu Panait, Karl Tuyls, Sean Luke