Robust, adaptive, modular ML | Montréal

A Text-Based Environment for Interactive Debugging In most existing approaches (shown in black), an agent rewrites its code conditioned on error messages obtained from executing its code. debug-gym equips the agent with additional tools such as pdb (shown in red),…

MSR contributions in the space of theoretical foundation for Offline RL Globally, MSR has made some recent advances in the space of the statistical foundations of Offline RL (opens in new tab), where a central question is to understand what…

In this page, we describe the algorithmic landscape of Offline RL and enumerate some algorithmic development efforts made by MSR in this space In a tutorial lecture (opens in new tab) on Offline RL (opens in new tab), we analyze its…

This page introduces the research area of Offline Reinforcement Learning (also sometimes called Batch Reinforcement Learning). It consists in training a target policy from a fixed dataset of trajectories collected with a behavioral policy. In comparison to classic Reinforcement Learning…