168 search results - page 1 / 34 » Optimism in Reinforcement Learning Based on Kullback-Leibler... |
CORR
2010
Springer
13 years 9 months ago
2010
Springer
We consider model-based reinforcement learning in finite Markov Decision Processes (MDPs), focussing on so-called optimistic strategies. Optimism is usually implemented by carryin...
PKDD
2010
Springer
13 years 8 months ago
2010
Springer
Partially observable Markov decision processes (POMDPs) are widely used for planning under uncertainty. In many applications, the huge size of the POMDP state space makes straightf...
CVPR
2005
IEEE
14 years 4 months ago
2005
IEEE
In this paper, we propose a novel learning method, called Jensen-Shannon Boosting (JSBoost) and demonstrate its application to object recognition. JSBoost incorporates Jensen-Shan...
BMCBI
2008
13 years 11 months ago
2008
Background: Machine-learning tools have gained considerable attention during the last few years for analyzing biological networks for protein function prediction. Kernel methods a...
ICONIP
2004
14 years 7 days ago
2004
Variational methods have proved popular and effective for inference and learning in intractable graphical models. An attractive feature of the approaches based on the Kullback-Lei...