188 citations · 880 across the 70 of their papers we have counts for
8 papers · 1 filter
Self-Imitation Advantage Learning
Johan Ferret, Olivier Pietquin, Matthieu Geist
Self-imitation learning is a Reinforcement Learning (RL) method that encourages actions whose returns were higher than expected, which helps in hard exploration and sparse reward p…
Munchausen Reinforcement Learning
Nino Vieillard, Olivier Pietquin, Matthieu Geist
Bootstrapping is a core mechanism in Reinforcement Learning (RL). Most algorithms, based on temporal differences, replace the true value of a transiting state by their current esti…
Fictitious Play for Mean Field Games: Continuous Time Analysis and Applications
Sarah Perrin, Julien Perolat, Mathieu Laurière +3
In this paper, we deepen the analysis of continuous time Fictitious Play learning algorithm to the consideration of various finite state Mean Field Game settings (finite horizon, $…
What Matters In On-Policy Reinforcement Learning? A Large-Scale Empirical Study
Marcin Andrychowicz, Anton Raichuk, Piotr Stańczyk +9
In recent years, on-policy reinforcement learning (RL) has been successfully applied to many different continuous control tasks. While RL algorithms are often conceptually simple,…
Show me the Way: Intrinsic Motivation from Demonstrations
Léonard Hussenot, Robert Dadashi, Matthieu Geist +1
The study of exploration in the domain of decision making has a long history but remains actively debated. From the vast literature that addressed this topic for decades under vari…
Primal Wasserstein Imitation Learning
Robert Dadashi, Léonard Hussenot, Matthieu Geist +1
Imitation Learning (IL) methods seek to match the behavior of an agent with that of an expert. In the present work, we propose a new IL method based on a conceptually simple algori…