121 citations · 407 across the 22 of their papers we have counts for
Showing 2019Show all
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cs.LG2019★ 95 cited
An Optimistic Perspective on Offline Reinforcement Learning
Rishabh Agarwal, Dale Schuurmans, Mohammad Norouzi
Off-policy reinforcement learning (RL) using a fixed offline dataset of logged interactions is an important consideration in real world applications. This paper studies offline RL…
cs.LG2019★ 69 cited
Learning to Generalize from Sparse and Underspecified Rewards
Rishabh Agarwal, Chen Liang, Dale Schuurmans +1
We consider the problem of learning from sparse and underspecified rewards, where an agent receives a complex input, such as a natural language instruction, and needs to generate a…
cs.AI2019
Evaluation Function Approximation for Scrabble
Rishabh Agarwal
The current state-of-the-art Scrabble agents are not learning-based but depend on truncated Monte Carlo simulations and the quality of such agents is contingent upon the time avail…