424 citations · 1.3k across the 15 of their papers we have counts for
4 papers · 1 filter
Deep Reinforcement Learning and its Neuroscientific Implications
Matthew Botvinick, Jane X. Wang, Will Dabney +2
The emergence of powerful artificial intelligence is defining new research directions in neuroscience. To date, this research has focused largely on deep neural networks trained us…
The Termination Critic
Anna Harutyunyan, Will Dabney, Diana Borsa +3
In this work, we consider the problem of autonomously discovering behavioral abstractions, or options, for reinforcement learning agents. We propose an algorithm that focuses on th…
Distributional Reinforcement Learning with Quantile Regression
Will Dabney, Mark Rowland, Marc G. Bellemare +1
In reinforcement learning an agent interacts with the environment by taking actions and observing the next state and reward. When sampled probabilistically, these state transitions…
Rainbow: Combining Improvements in Deep Reinforcement Learning
Matteo Hessel, Joseph Modayil, Hado van Hasselt +7
The deep reinforcement learning community has made several independent improvements to the DQN algorithm. However, it is unclear which of these extensions are complementary and can…