Gabriel Dulac-Arnold

RL Unplugged: Benchmarks for Offline Reinforcement Learning.

2020 · arXiv (Cornell University)

Offline methods for reinforcement learning have a potential to help bridge the gap between reinforcement learning research and real-world applications. They make it possible to learn policies from offline datasets, thus overcoming concerns associated with …

A Geometric Perspective on Self-Supervised Policy Adaptation

2020 · arXiv (Cornell University)

One of the most challenging aspects of real-world reinforcement learning (RL) is the multitude of unpredictable and ever-changing distractions that could divert an agent from what was tasked to do in its training environment. While …