687 citations · 3k across the 109 of their papers we have counts for
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cs.AI2015★ 51 cited
Deep Reinforcement Learning in Parameterized Action Space
Matthew Hausknecht, Peter Stone
Recent work has shown that deep neural networks are capable of approximating both value functions and policies in reinforcement learning domains featuring continuous state and acti…
cs.LG2015★ 687 cited
Deep Recurrent Q-Learning for Partially Observable MDPs
Matthew Hausknecht, Peter Stone
Deep Reinforcement Learning has yielded proficient controllers for complex tasks. However, these controllers have limited memory and rely on being able to perceive the complete gam…
cs.AI2015★ 9 cited
Representative Selection in Non Metric Datasets
Elad Liebman, Benny Chor, Peter Stone
This paper considers the problem of representative selection: choosing a subset of data points from a dataset that best represents its overall set of elements. This subset needs to…