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Provably Near-Optimal Sampling-Based Policies for Stochastic...
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Provably Near-Optimal Sampling-Based Policies for Stochastic Inventory Control Models
13 years 6 months ago
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legacy.orie.cornell.edu
Retsef Levi, Robin Roundy, David B. Shmoys
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IJCAI
2001
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Artificial Intelligence
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R-MAX - A General Polynomial Time Algorithm for Near-Optimal Reinforcement Learning
13 years 8 months ago
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jmlr.csail.mit.edu
R-max is a very simple model-based reinforcement learning algorithm which can attain near-optimal average reward in polynomial time. In R-max, the agent always maintains a complet...
Ronen I. Brafman, Moshe Tennenholtz
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