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Policy and value iteration both require you to, for each possible transition and each corresponding possible reward at each state, compute a statistic of $r + \gamma V(s')$. In order for this to be tractable, you need for there to be at most finitely many states, actions, possible rewards, and possible transitions at each state. You also need to know the ...


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Wow, that's a really confusing example, if I were you I would check out some other RL resources. I wouldn't consider h being the last step and h-1 being the previous step. In terms of steps of iterations of the dynamic programming algorithm, h is actually the first step, h-1 the next step and so on. Viewing it in these terms it makes sense that the Value of ...


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