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Results tagged with reinforce
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user 54134
For questions related to the REINFORCE algorithm (or update rule), which is a policy gradient algorithm, that is, an algorithm which estimates the policy directly (that is, without first estimating any value function).
2
votes
Accepted
Should the concept of discounted rewards result in multiple arrays per episode in RL?
because it will take into account all future rewards almost at their full value, whereas if $\gamma$ is close to 0, $G_k$ will be close to 1, i.e. it will take into account just the first reward
Now, in REINFORCE …
4
votes
Accepted
What modifications can maximize the efficacy of the REINFORCE algorithm for a policy gradien...
One simple improvement over the REINFORCE algorithm you've linked to is to use the advantage function instead of the normalised cumulative discounted return. … In your implementation of REINFORCE, the gradient of the loss is calculated as:
$$
L(\theta) = -\sum_{t=0}^T\hat{G}_t\log(\pi_\theta(a_t|s_t))
$$
with
$$\hat{G}_t = \frac{\sum_{k=0}^t r_k - \hat{r}}{\hat …