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For questions related to the concept of Markov decision process (MDP), which is a mathematical framework for modeling decision making in situations where outcomes are partly random and partly under the control of a decision-maker. The concept of MDP is useful for studying optimization problems solved via dynamic programming and reinforcement learning.

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I have been reading about discounted MDPs and Stochastic Shortest Path (SSP). I recently came to know (from a friend) that every discounted MDP can be converted to an equivalent SSP but not the other …
asked Apr 12 '21 by user529295
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Most RL books (Sutton & Barto, Bertsekas, etc.) talk about policy iteration for infinite-horizon MDPs. Does the policy iteration convergence hold for finite-horizon MDP? If yes, how can we derive the …
asked Apr 14 '21 by user529295