papers
Publications (12)
cs.AI2018
The Reactor: A fast and sample-efficient Actor-Critic agent for Reinforcement Learning
Audrunas Gruslys, Will Dabney, Mohammad Gheshlaghi Azar +3
cs.AI2018
Leveraging Demonstrations for Deep Reinforcement Learning on Robotics Problems with Sparse Rewards
Mel Vecerik, Todd Hester, Jonathan Scholz +7
cs.AI2017
Deep Q-learning from Demonstrations
Todd Hester, Matej Vecerik, Olivier Pietquin +11
cs.AI2019
World Discovery Models
Mohammad Gheshlaghi Azar, Bilal Piot, Bernardo Avila Pires +3
cs.AI2017
Rainbow: Combining Improvements in Deep Reinforcement Learning
Matteo Hessel, Joseph Modayil, Hado van Hasselt +7
cs.CL2017
End-to-end optimization of goal-driven and visually grounded dialogue systems
Florian Strub, Harm de Vries, Jeremie Mary +3
cs.LG2017
Observational Learning by Reinforcement Learning
Diana Borsa, Bilal Piot, Rémi Munos +1
cs.GT2017
Learning Nash Equilibrium for General-Sum Markov Games from Batch Data
Julien Pérolat, Florian Strub, Bilal Piot +1
math.OC2016
Difference of Convex Functions Programming Applied to Control with Expert Data
Bilal Piot, Matthieu Geist, Olivier Pietquin
cs.LG2018
Playing the Game of Universal Adversarial Perturbations
Julien Perolat, Mateusz Malinowski, Bilal Piot +1
cs.LG2018
Observe and Look Further: Achieving Consistent Performance on Atari
Tobias Pohlen, Bilal Piot, Todd Hester +10
cs.LG2017
Is the Bellman residual a bad proxy?
Matthieu Geist, Bilal Piot, Olivier Pietquin