21 search results - page 1 / 5 » Bayesian reinforcement learning in continuous POMDPs with ga... |
152
Voted
IROS
2009
IEEE
15 years 10 months ago
2009
IEEE
— Partially Observable Markov Decision Processes (POMDPs) provide a rich mathematical model to handle realworld sequential decision processes but require a known model to be solv...
133
Voted
ICRA
2008
IEEE
15 years 9 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...
172
Voted
PKDD
2010
Springer
15 years 1 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...
155
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NIPS
2007
15 years 4 months ago
2007
Bayesian Reinforcement Learning has generated substantial interest recently, as it provides an elegant solution to the exploration-exploitation trade-off in reinforcement learning...
138
Voted
ICML
2005
IEEE
16 years 4 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...