9 citations · 15 across the 4 of their papers we have counts for
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cs.RO2019
Unsupervised Learning and Exploration of Reachable Outcome Space
Giuseppe Paolo, Alban Laflaquière, Alexandre Coninx +1
Performing Reinforcement Learning in sparse rewards settings, with very little prior knowledge, is a challenging problem since there is no signal to properly guide the learning pro…
cs.RO2017★ 6 cited
Towards continuous control of flippers for a multi-terrain robot using deep reinforcement learning
Giuseppe Paolo, Lei Tai, Ming Liu
In this paper we focus on developing a control algorithm for multi-terrain tracked robots with flippers using a reinforcement learning (RL) approach. The work is based on the deep…