Bayesian exploration in Markov decision processes
Markov Decision Processes are a mathematical framework widely used for stochastic optimization and control problems. Reinforcement Learning is a branch of Artificial Intelligence that deals with stochastic environments where the dynamics of the system are unknown. A major issue for learning algorit...
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| Format: | Others |
| Language: | en |
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McGill University
2007
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| Online Access: | http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=18479 |