17 search results - page 3 / 4 » Smarter Sampling in Model-Based Bayesian Reinforcement Learn... |
ICML
2000
IEEE
15 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...
ICRA
2008
IEEE
15 years 4 months ago
2008
IEEE
— We consider the problem of optimal control in continuous and partially observable environments when the parameters of the model are not known exactly. Partially Observable Mark...
ICML
2010
IEEE
14 years 7 months ago
2010
IEEE
Temporal difference (TD) algorithms are attractive for reinforcement learning due to their ease-of-implementation and use of "bootstrapped" return estimates to make effi...
ICML
2009
IEEE
15 years 10 months ago
2009
IEEE
We consider the exploration/exploitation problem in reinforcement learning (RL). The Bayesian approach to model-based RL offers an elegant solution to this problem, by considering...
87
Voted
NIPS
2008
14 years 11 months ago
2008
In kernel-based regression learning, optimizing each kernel individually is useful when the data density, curvature of regression surfaces (or decision boundaries) or magnitude of...