582 search results - page 19 / 117 » Gaussian Processes in Reinforcement Learning |
ICML
2005
IEEE
14 years 10 months ago
2005
IEEE
When monitoring spatial phenomena, which are often modeled as Gaussian Processes (GPs), choosing sensor locations is a fundamental task. A common strategy is to place sensors at t...
ICML
2004
IEEE
14 years 10 months ago
2004
IEEE
Many real-world classification tasks involve the prediction of multiple, inter-dependent class labels. A prototypical case of this sort deals with prediction of a sequence of labe...
ESSMAC
2003
Springer
14 years 2 months ago
2003
Springer
Gaussian Process prior models, as used in Bayesian non-parametric statistical models methodology are applied to implement a nonlinear adaptive control law. The expected value of a...
FSTTCS
2006
Springer
14 years 1 months ago
2006
Springer
We propose a new approach to verification of probabilistic processes for which the model may not be available. We use a technique from Reinforcement Learning to approximate how far...
NN
2010
Springer
13 years 4 months ago
2010
Springer
Appropriately designing sampling policies is highly important for obtaining better control policies in reinforcement learning. In this paper, we first show that the least-squares ...