112 citations · 143 across the 5 of their papers we have counts for
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cs.LG2020★ 12 cited
Active Reinforcement Learning: Observing Rewards at a Cost
David Krueger, Jan Leike, Owain Evans +1
Active reinforcement learning (ARL) is a variant on reinforcement learning where the agent does not observe the reward unless it chooses to pay a query cost c > 0. The central ques…
cs.LG2019★ 9 cited
Generalizing from a few environments in safety-critical reinforcement learning
Zachary Kenton, Angelos Filos, Owain Evans +1
Before deploying autonomous agents in the real world, we need to be confident they will perform safely in novel situations. Ideally, we would expose agents to a very wide range of…
cs.LG2018
Active Reinforcement Learning with Monte-Carlo Tree Search
Sebastian Schulze, Owain Evans
Active Reinforcement Learning (ARL) is a twist on RL where the agent observes reward information only if it pays a cost. This subtle change makes exploration substantially more cha…