GECCO
2009
Springer
13 years 2 months ago
2009
Springer
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...
ESANN
2008
13 years 5 months ago
2008
Natural policy gradient methods and the covariance matrix adaptation evolution strategy, two variable metric methods proposed for solving reinforcement learning tasks, are contrast...
EWRL
2008
13 years 6 months ago
2008
Two variable metric reinforcement learning methods, the natural actor-critic algorithm and the covariance matrix adaptation evolution strategy, are compared on a conceptual level a...
GECCO
2006
Springer
13 years 8 months ago
2006
Springer
First, the covariance matrix adaptation (CMA) with rankone update is introduced into the (1+1)-evolution strategy. An improved implementation of the 1/5-th success rule is propose...
EMO
2006
Springer
13 years 8 months ago
2006
Springer
The multi-objective covariance matrix adaptation evolution strategy (MO-CMA-ES) combines a mutation operator that adapts its search distribution to the underlying optimization prob...
GECCO
2010
Springer
13 years 8 months ago
2010
Springer
The multi-objective covariance matrix adaptation evolution strategy (MO-CMA-ES) is an evolutionary algorithm for continuous vector-valued optimization. It combines indicator-based...
PPSN
2004
Springer
13 years 9 months ago
2004
Springer
Abstract. Evolution Strategies, Evolutionary Algorithms based on Gaussian mutation and deterministic selection, are today considered the best choice as far as parameter optimizatio...
CEC
2005
IEEE
13 years 10 months ago
2005
IEEE
Abstract- Evolutionary Algorithms (EAs) have the tendency to converge quickly into a single solution in the search space. However, many complex search problems require the identiï¬...
CEC
2008
IEEE
13 years 10 months ago
2008
IEEE
Abstract—While scalarization approaches to multicriteria optimization become infeasible in the case of many objectives, for few objectives the beneï¬ts of populationbased method...
EVOW
2010
Springer
13 years 10 months ago
2010
Springer
For many real-life engineering optimization problems, the cost of one objective function evaluation can take several minutes or hours. In this context, a popular approach to reduce...