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GECCO
2009
Springer
162views Optimization» more  GECCO 2009»
14 years 8 months ago
Uncertainty handling CMA-ES for reinforcement learning
The covariance matrix adaptation evolution strategy (CMAES) has proven to be a powerful method for reinforcement learning (RL). Recently, the CMA-ES has been augmented with an ada...
Verena Heidrich-Meisner, Christian Igel
GECCO
2009
Springer
123views Optimization» more  GECCO 2009»
15 years 4 months ago
Alternative voting systems in stock car racing
The National Association for Stock Car Auto Racing (NASCAR) is currently the No. 1 spectator sport in the United States. However, the manner in which drivers are ranked to determi...
Aaron Garrett, Daniel Eric Smith
GECCO
2009
Springer
194views Optimization» more  GECCO 2009»
15 years 4 months ago
Combining evolution strategy and gradient descent method for discriminative learning of bayesian classifiers
The optimization method is one of key issues in discriminative learning of pattern classifiers. This paper proposes a hybrid approach of the Covariance Matrix Adaptation Evolution...
Xuefeng Chen, Xiabi Liu, Yunde Jia
GECCO
2009
Springer
15 years 4 months ago
Evolution of team composition in multi-agent systems
Evolution of multi-agent teams has been shown to be an effective method of solving complex problems involving the exploration of an unknown problem space. These autonomous and het...
Joshua Rubini, Robert B. Heckendorn, Terence Soule
75
Voted
GECCO
2009
Springer
169views Optimization» more  GECCO 2009»
15 years 2 months ago
An ant based algorithm for task allocation in large-scale and dynamic multiagent scenarios
This paper addresses the problem of multiagent task allocation in extreme teams. An extreme team is composed by a large number of agents with overlapping functionality operating i...
Fernando dos Santos, Ana L. C. Bazzan