SmoothCruiser achieves O~(1/epsilon^4) problem-independent sample complexity for value estimation in entropy-regularized MDPs and games via a generative model.
http://ggp.stanford.edu/readings/uct.pdf Bandit-based Monte-Carlo planning
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Planning in entropy-regularized Markov decision processes and games
SmoothCruiser achieves O~(1/epsilon^4) problem-independent sample complexity for value estimation in entropy-regularized MDPs and games via a generative model.