2 code implementations • 23 Oct 2019 • Reda Bahi Slaoui, William R. Clements, Jakob N. Foerster, Sébastien Toth
Producing agents that can generalize to a wide range of visually different environments is a significant challenge in reinforcement learning.
no code implementations • 25 Sep 2019 • Reda Bahi Slaoui, William R. Clements, Jakob N. Foerster, Sébastien Toth
In this work, we formalize the domain randomization problem, and show that minimizing the policy's Lipschitz constant with respect to the randomization parameters leads to low variance in the learned policies.
2 code implementations • 23 May 2019 • William R. Clements, Bastien Van Delft, Benoît-Marie Robaglia, Reda Bahi Slaoui, Sébastien Toth
Reinforcement learning agents are faced with two types of uncertainty.