183 citations · 184 across the 3 of their papers we have counts for
3 papers
A Survey of Temporal Credit Assignment in Deep Reinforcement Learning
Eduardo Pignatelli, Johan Ferret, Matthieu Geist +4
The Credit Assignment Problem (CAP) refers to the longstanding challenge of Reinforcement Learning (RL) agents to associate actions with their long-term consequences. Solving the C…
Exploration via Epistemic Value Estimation
Simon Schmitt, John Shawe-Taylor, Hado van Hasselt
How to efficiently explore in reinforcement learning is an open problem. Many exploration algorithms employ the epistemic uncertainty of their own value predictions -- for instance…
Successor Features for Transfer in Reinforcement Learning
André Barreto, Will Dabney, Rémi Munos +4
Transfer in reinforcement learning refers to the notion that generalization should occur not only within a task but also across tasks. We propose a transfer framework for the scena…