# Questions tagged [policy-evaluation]

For questions related to the various policy evaluation (PE) algorithms, which are numerical iterative algorithms that are used to find the value function associated with a given policy, which is often denoted as the "prediction problem". PE is also considered a dynamic programming method, which is regularly discussed in reinforcement learning textbooks.

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### Difficulty understanding Monte Carlo policy evaluation (state-value) for gridworld

I've been trying to read Sutton & Barto book chapter 5.1, but I'm still a bit confused about the procedure of using Monte Carlo policy evaluation (p.92), and now I just cant proceed anymore coding ...
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### How to measure accuracy of learned value function of a fixed policy?

Let's say we've a given policy whose value function is to be evaluated. One way to get the value function can be using expected SARSA, as in this stack exchange answer. However, my MDP's state space ...
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The iterative update rule for policy evaluation that is, approximating the value function for a given policy is: $$v^{k+1} = r_{\pi} + \gamma P_{\pi}v^{k}$$ This is the simultaneous update rule where ...