1 citations · 1 across the 2 of their papers we have counts for
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Don't Do What Doesn't Matter: Intrinsic Motivation with Action Usefulness
Mathieu Seurin, Florian Strub, Philippe Preux +1
Sparse rewards are double-edged training signals in reinforcement learning: easy to design but hard to optimize. Intrinsic motivation guidances have thus been developed toward alle…
HIGhER : Improving instruction following with Hindsight Generation for Experience Replay
Geoffrey Cideron, Mathieu Seurin, Florian Strub +1
Language creates a compact representation of the world and allows the description of unlimited situations and objectives through compositionality. While these characterizations may…
I'm sorry Dave, I'm afraid I can't do that, Deep Q-learning from forbidden action
Mathieu Seurin, Philippe Preux, Olivier Pietquin
The use of Reinforcement Learning (RL) is still restricted to simulation or to enhance human-operated systems through recommendations. Real-world environments (e.g. industrial robo…