5 search results - page 1 / 1 » Gaussian Processes for Sample Efficient Reinforcement Learni... |
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...
NN
2010
Springer
13 years 2 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 ...
EWRL
2008
13 years 9 months ago
2008
We consider reinforcement learning in the parameterized setup, where the model is known to belong to a parameterized family of Markov Decision Processes (MDPs). We further impose ...
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...
NIPS
2008
13 years 9 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...