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GECCO
2006
Springer
156views Optimization» more  GECCO 2006»
13 years 9 months ago
A computational efficient covariance matrix update and a (1+1)-CMA for evolution strategies
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...
Christian Igel, Thorsten Suttorp, Nikolaus Hansen
EMO
2009
Springer
159views Optimization» more  EMO 2009»
13 years 12 months ago
Recombination for Learning Strategy Parameters in the MO-CMA-ES
The multi-objective covariance matrix adaptation evolution strategy (MO-CMA-ES) is a variable-metric algorithm for real-valued vector optimization. It maintains a parent population...
Thomas Voß, Nikolaus Hansen, Christian Igel
GECCO
2009
Springer
162views Optimization» more  GECCO 2009»
13 years 3 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
ESANN
2008
13 years 6 months ago
Similarities and differences between policy gradient methods and evolution strategies
Natural policy gradient methods and the covariance matrix adaptation evolution strategy, two variable metric methods proposed for solving reinforcement learning tasks, are contrast...
Verena Heidrich-Meisner, Christian Igel
EMO
2006
Springer
172views Optimization» more  EMO 2006»
13 years 9 months ago
Steady-State Selection and Efficient Covariance Matrix Update in the Multi-objective CMA-ES
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...
Christian Igel, Thorsten Suttorp, Nikolaus Hansen