13 search results - page 1 / 3 » Efficient Uncertainty Propagation for Reinforcement Learning... |
ICANN
2009
Springer
13 years 11 months ago
2009
Springer
In a typical reinforcement learning (RL) setting details of the environment are not given explicitly but have to be estimated from observations. Most RL approaches only optimize th...
IJCNN
2008
IEEE
14 years 2 months ago
2008
IEEE
— In this paper we address the reliability of policies derived by Reinforcement Learning on a limited amount of observations. This can be done in a principled manner by taking in...
PKDD
2010
Springer
13 years 5 months ago
2010
Springer
Abstract. We present an implementation of model-based online reinforcement learning (RL) for continuous domains with deterministic transitions that is specifically designed to achi...
JMLR
2010
13 years 2 months ago
2010
We consider reinforcement learning as solving a Markov decision process with unknown transition distribution. Based on interaction with the environment, an estimate of the transit...
ALT
2003
Springer
13 years 11 months ago
2003
Springer
Abstract. Inductive inference can be considered as one of the fundamental paradigms of algorithmic learning theory. We survey results recently obtained and show their impact to pot...