34 citations · 39 across the 4 of their papers we have counts for
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cs.LG2019★ 34 cited
Investigating Generalisation in Continuous Deep Reinforcement Learning
Chenyang Zhao, Olivier Sigaud, Freek Stulp +1
Deep Reinforcement Learning has shown great success in a variety of control tasks. However, it is unclear how close we are to the vision of putting Deep RL into practice to solve r…
cs.LG2018
Policy Search in Continuous Action Domains: an Overview
Olivier Sigaud, Freek Stulp
Continuous action policy search is currently the focus of intensive research, driven both by the recent success of deep reinforcement learning algorithms and the emergence of compe…