4544 search results - page 75 / 909 » Reinforcement Learning with Time |
ICML
2000
IEEE
14 years 1 months 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...
AAMAS
2007
Springer
13 years 9 months ago
2007
Springer
In this paper, we investigate the use of parallelization in reinforcement learning (RL), with the goal of learning optimal policies for single-agent RL problems more quickly by us...
ICML
2008
IEEE
14 years 9 months ago
2008
IEEE
Rich representations in reinforcement learning have been studied for the purpose of enabling generalization and making learning feasible in large state spaces. We introduce Object...
ICML
2005
IEEE
14 years 9 months ago
2005
IEEE
Gaussian Process Temporal Difference (GPTD) learning offers a Bayesian solution to the policy evaluation problem of reinforcement learning. In this paper we extend the GPTD framew...
TFS
2011
13 years 3 months ago
2011
—Reinforcement learning (RL) is a valuable learning method when the systems require a selection of control actions whose consequences emerge over long periods for which input– ...