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GECCO
2009
Springer
162views Optimization» more  GECCO 2009»
13 years 2 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
PPSN
2010
Springer
13 years 2 months ago
A Natural Evolution Strategy for Multi-objective Optimization
Abstract. The recently introduced family of natural evolution strategies (NES), a novel stochastic descent method employing the natural gradient, is providing a more principled alt...
Tobias Glasmachers, Tom Schaul, Jürgen Schmid...
CEC
2007
IEEE
13 years 8 months ago
Identification of the isotherm function in chromatography using CMA-ES
This paper deals with the identification of the flux for a system of conservation laws in the specific example of analytic chromatography. The fundamental equations of chromatograp...
Mohamed Jebalia, Anne Auger, Marc Schoenauer, F. J...
GECCO
2010
Springer
195views Optimization» more  GECCO 2010»
13 years 8 months ago
Improved step size adaptation for the MO-CMA-ES
The multi-objective covariance matrix adaptation evolution strategy (MO-CMA-ES) is an evolutionary algorithm for continuous vector-valued optimization. It combines indicator-based...
Thomas Voß, Nikolaus Hansen, Christian Igel