New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

derivation of stochastic approximation and its use #4

Open

mzaffalon opened this issue Jun 10, 2023 · 0 comments

Owner

mzaffalon commented Jun 10, 2023 •

edited

Loading

How is the stochastic iteration $q_{k+1} = q_k - \alpha_k e(q_k)$ derived?

How is it applied to TD-learning? How are the validity conditions on $e(q)$ satisfied?

Ref: questions on Moodle 1, 2

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment