Search Results
| Search type | Search syntax |
|---|---|
| Tags | [tag] |
| Exact | "words here" |
| Author |
user:1234 user:me (yours) |
| Score |
score:3 (3+) score:0 (none) |
| Answers |
answers:3 (3+) answers:0 (none) isaccepted:yes hasaccepted:no inquestion:1234 |
| Views | views:250 |
| Code | code:"if (foo != bar)" |
| Sections |
title:apples body:"apples oranges" |
| URL | url:"*.example.com" |
| Saves | in:saves |
| Status |
closed:yes duplicate:no migrated:no wiki:no |
| Types |
is:question is:answer |
| Exclude |
-[tag] -apples |
| For more details on advanced search visit our help page | |
Results tagged with policy-evaluation
Search options answers only
not deleted
user 1847
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.
1
vote
Why does my implementation of TD(0) not work?
It is a very simple example with terminal states s2 and s3 and it is clear that the Value function should converge to:
V(s1) = 1, V(s2) = -1, V(s3) = 1
which my implementations of MC and DP do, so …
- 33.3k
1
vote
Accepted
Can we use Q-learning update for policy evaluation (not control)?
For off-policy learning you must have two policies - a behaviour policy and a target policy. If the two policies are the same, then you end up with SARSA, not Q learning.
You cannot use Q learning dir …
- 33.3k
0
votes
Accepted
Why is the update in-place faster than the out-of-place one in dynamic programming?
When you make updates in-place, then some of the entries in state_values[next_i, next_j] that you are referencing here
value += ACTION_PROB * (reward + discount * state_values[next_i, next_j])
will a …
- 33.3k
1
vote
Accepted
Do I really need to do policy evaluation until convergence in policy iteration?
I don't understand why policy evaluation needs to be done until convergence
It doesn't need to be, although the resulting algorithm if you cut short of convergence is not strictly policy iteration a …
- 33.3k
3
votes
Why do we need to go back to policy evaluation after policy improvement if the policy is not...
There is a difference between accurate value function estimates, and optimal value functions. An optimal value function is more specifically the value function of an optimal policy.
Value functions ar …
- 33.3k
4
votes
Accepted
Why is update rule of the value function different in policy evaluation and policy iteration?
Yes, the two update equations are equivalent. As an aside, technically the equation you give is not the Bellman equation, but the update step re-written as an equation - in the Bellman equation instea …
- 33.3k