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GECCO
2009
Springer
162views Optimization» more  GECCO 2009»
13 years 6 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
CSE
2009
IEEE
14 years 3 months ago
Reinforcement Learning of Listener Response for Mood Classification of Audio
This paper describes a method of applying a reinforcement learning artificial intelligence to categorize audio files by mood based on listener response during a performance. The s...
Jack Stockholm, Philippe Pasquier
AI
2006
Springer
14 years 20 days ago
Trace Equivalence Characterization Through Reinforcement Learning
In the context of probabilistic verification, we provide a new notion of trace-equivalence divergence between pairs of Labelled Markov processes. This divergence corresponds to the...
Josee Desharnais, François Laviolette, Kris...
AAAI
2007
13 years 11 months ago
A Reinforcement Learning Algorithm with Polynomial Interaction Complexity for Only-Costly-Observable MDPs
An Unobservable MDP (UMDP) is a POMDP in which there are no observations. An Only-Costly-Observable MDP (OCOMDP) is a POMDP which extends an UMDP by allowing a particular costly a...
Roy Fox, Moshe Tennenholtz
ICPR
2006
IEEE
14 years 10 months ago
Control Double Inverted Pendulum by Reinforcement Learning with Double CMAC Network
To accelerate the learning of reinforcement learning, many types of function approximation are used to represent state value. However function approximation reduces the accuracy o...
Siwei Luo, Yu Zheng, Ziang Lv