Skip to content
/ RPVL Public
forked from kishanpb/RobustRL

Code for Improved Sample Complexity Bounds for Distributionally Robust Reinforcement Learning [AISTATS'23]

License

Notifications You must be signed in to change notification settings

zaiyan-x/RPVL

This branch is 3 commits ahead of kishanpb/RobustRL:main.

Folders and files

NameName
Last commit message
Last commit date

Latest commit

Oct 27, 2023
529794e · Oct 27, 2023

History

5 Commits
Oct 27, 2023
Feb 1, 2023
Oct 15, 2022

Repository files navigation

Improved Sample Complexity Bounds for Distributionally Robust Reinforcement Learning

This repository is a study of interesting characteristics of the robust value iteration algorithm. In particular, we introduce RPVL in our paper which considers finite-horizon tabular MDP. Gambler's problem (or Gambler's Ruin) is a simple yet nice example for us to characterize the behavior of an optimal robust policy.

About

Code for Improved Sample Complexity Bounds for Distributionally Robust Reinforcement Learning [AISTATS'23]

Topics

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Jupyter Notebook 100.0%