1.3k citations · 4.8k across the 58 of their papers we have counts for
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On Bonus-Based Exploration Methods in the Arcade Learning Environment
Adrien Ali Taïga, William Fedus, Marlos C. Machado +2
Research on exploration in reinforcement learning, as applied to Atari 2600 game-playing, has emphasized tackling difficult exploration problems such as Montezuma's Revenge (Bellem…
Deep Reinforcement Learning at the Edge of the Statistical Precipice
Rishabh Agarwal, Max Schwarzer, Pablo Samuel Castro +2
Deep reinforcement learning (RL) algorithms are predominantly evaluated by comparing their relative performance on a large suite of tasks. Most published results on deep RL benchma…
Metrics and continuity in reinforcement learning
Charline Le Lan, Marc G. Bellemare, Pablo Samuel Castro
In most practical applications of reinforcement learning, it is untenable to maintain direct estimates for individual states; in continuous-state systems, it is impossible. Instead…
Contrastive Behavioral Similarity Embeddings for Generalization in Reinforcement Learning
Rishabh Agarwal, Marlos C. Machado, Pablo Samuel Castro +1
Reinforcement learning methods trained on few environments rarely learn policies that generalize to unseen environments. To improve generalization, we incorporate the inherent sequ…