53 citations · 147 across the 20 of their papers we have counts for
4 papers · 1 filter
Implicit Under-Parameterization Inhibits Data-Efficient Deep Reinforcement Learning
Aviral Kumar, Rishabh Agarwal, Dibya Ghosh +1
We identify an implicit under-parameterization phenomenon in value-based deep RL methods that use bootstrapping: when value functions, approximated using deep neural networks, are…
Representations for Stable Off-Policy Reinforcement Learning
Dibya Ghosh, Marc G. Bellemare
Reinforcement learning with function approximation can be unstable and even divergent, especially when combined with off-policy learning and Bellman updates. In deep reinforcement…
An operator view of policy gradient methods
Dibya Ghosh, Marlos C. Machado, Nicolas Le Roux
We cast policy gradient methods as the repeated application of two operators: a policy improvement operator , which maps any policy to a better one ,…
On Catastrophic Interference in Atari 2600 Games
William Fedus, Dibya Ghosh, John D. Martin +3
Model-free deep reinforcement learning is sample inefficient. One hypothesis -- speculated, but not confirmed -- is that catastrophic interference within an environment inhibits le…