286 search results - page 12 / 58 » Using inaccurate models in reinforcement learning |
ICML
2000
IEEE
14 years 1 days ago
2000
IEEE
The reinforcement learning problem can be decomposed into two parallel types of inference: (i) estimating the parameters of a model for the underlying process; (ii) determining be...
ICML
2006
IEEE
14 years 8 months ago
2006
IEEE
For a Markov Decision Process with finite state (size S) and action spaces (size A per state), we propose a new algorithm--Delayed Q-Learning. We prove it is PAC, achieving near o...
ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
We consider the problem of multi-task reinforcement learning where the learner is provided with a set of tasks, for which only a small number of samples can be generated for any g...
ICML
2007
IEEE
14 years 8 months ago
2007
IEEE
We consider the problem of multi-task reinforcement learning, where the agent needs to solve a sequence of Markov Decision Processes (MDPs) chosen randomly from a fixed but unknow...
CSL
2012
Springer
12 years 3 months ago
2012
Springer
Reinforcement techniques have been successfully used to maximise the expected cumulative reward of statistical dialogue systems. Typically, reinforcement learning is used to estim...