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Microsoft
Monte Carlo Methods for Bayesian Reinforcement Learning and POMDP
Partially Observable Markov Decision Process is an elegant and general model for planning under uncertainty. Applications for POMDPs include control of autonomous vehicles, dialog systems, and systems for providing assistance to the elderly. Learning problems such as reinforcement learning, making recommendations and active learning can also be ...
Aug 23, 2012
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