Bayesian Reinforcement Learning via Deep, Sparse Sampling

7 Feb 2019Divya GroverDebabrota BasuChristos Dimitrakakis

We address the problem of Bayesian reinforcement learning using efficient model-based online planning. We propose an optimism-free Bayes-adaptive algorithm to induce deeper and sparser exploration with a theoretical bound on its performance relative to the Bayes optimal policy, with a lower computational complexity... (read more)

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