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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1answer
53 views

Is existence and uniqueness of state-value function at $\gamma < 1$ theoretical?

Consider the following statement from 4.1 Policy Evaluation of the first edition of Sutton and Barto's book. The existence and uniqueness of $V^{\pi}$ are guaranteed as long as either $\gamma < 1$...
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1answer
25 views

Using states (features) and actions from a heuristic model to estimate the value function of a reinforcement learning agent [closed]

new to RL here. As far as i understood from RL courses, that there is two sides of reinforcement learning. Policy Evaluation, which is the task of knowing the value function for certain policy. and ...
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0answers
13 views

Extracting the approximate pareto front for a MORL implementation of Deep Sea Treasure

I've recently been looking into multi-objective reinforcement learning problems for college, mainly the MO Deep Sea Treasure problem discussed here. I'm applying a single policy algorithm called w-...
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1answer
43 views

Why is the update in-place faster than the out-of-place one in dynamic programming?

In Barto and Sutton's book, it's written that we have two types of updates in dynamic programming Update out-of-place Update in-place The update in-place is the faster one. Why is that the case? ...
2
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1answer
54 views

Can we use Q-learning update for policy evaluation (not control)?

For policy evaluation purposes, can we use the Q-learning algorithm even though, technically, it is meant for control? Maybe like this: Have the policy to be evaluated as the behaviour policy. Update ...
2
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1answer
41 views

Why do we need to go back to policy evaluation after policy improvement if the policy is not stable?

Above is the algorithm for Policy Iteration from Sutton's RL book. So, step 2 actually looks like value iteration, and then, at step 3 (policy improvement), if the policy isn't stable it goes back to ...
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1answer
79 views

Is value iteration stopped after one update of each state?

In section 4.4 Value Iteration, the authors write One important special case is when policy evaluation is stopped after just one sweep (one update of each state). This algorithm is called value ...
4
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1answer
213 views

Why is update rule of the value function different in policy evaluation and policy iteration?

In the textbook "Reinforcement Learning: An Introduction", by Richard Sutton and Andrew Barto, the pseudo code for Policy Evaluation is given as follows: The update equation for $V(s)$ comes from the ...
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2answers
731 views

What is the proof that policy evaluation converges to the optimal solution?

Although I know how the algorithm of iterative policy evaluation using dynamic programming works, I am having a hard time realizing how it actually converges. It appeals to intuition that, with each ...
2
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1answer
51 views

How can I implement policy evaluation when reward is tied to an action outcome?

I'm following Stanford reinforcement learning videos on youtube. One of the assignments asks to write code for policy evaluation for Gym's FrozenLake-v0 environment. In the course (and books I have ...
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3answers
264 views

Why can the Bellman equation be turned into an update rule?

In chapter 4.1 of Sutton's book, the Bellman equation is turned into an update rule by simply changing the indices of it. How is it mathematically justified? I didn't quite get the initiation of why ...
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1answer
105 views

Why isn't the implementation of my policy evaluation for a simple MDP converging?

I am trying to code out a policy evaluation algorithm to find the $V^\pi(s)$ for all states. The following diagram below shows the MDP. In this case i let p = q = 0.5. the rewards for each states ...
4
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1answer
88 views

How does policy evaluation work for continuous state space model-free approaches?

How does policy evaluation work for continuous state space model-free approaches? Theoretically, a model-based approach for the discrete state and action space can be computed via dynamic programming ...
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0answers
413 views

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 ...