14 citations · 18 across the 2 of their papers we have counts for
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cs.LG2018
Directed Policy Gradient for Safe Reinforcement Learning with Human Advice
Hélène Plisnier, Denis Steckelmacher, Tim Brys +2
Many currently deployed Reinforcement Learning agents work in an environment shared with humans, be them co-workers, users or clients. It is desirable that these agents adjust to p…
cs.LG2015★ 14 cited
Using PCA to Efficiently Represent State Spaces
William Curran, Tim Brys, Matthew Taylor +1
Reinforcement learning algorithms need to deal with the exponential growth of states and actions when exploring optimal control in high-dimensional spaces. This is known as the cur…