4 citations · 5 across the 3 of their papers we have counts for
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cs.AI2021
Is Policy Learning Overrated?: Width-Based Planning and Active Learning for Atari
Benjamin Ayton, Masataro Asai
Width-based planning has shown promising results on Atari 2600 games using pixel input, while using substantially fewer environment interactions than reinforcement learning. Recent…
cs.AI2018★ 4 cited
Vulcan: A Monte Carlo Algorithm for Large Chance Constrained MDPs with Risk Bounding Functions
Benjamin J Ayton, Brian C Williams
Chance Constrained Markov Decision Processes maximize reward subject to a bounded probability of failure, and have been frequently applied for planning with potentially dangerous o…