52 citations · 100 across the 6 of their papers we have counts for
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cs.RO2020★ 4 cited
Solving Challenging Dexterous Manipulation Tasks With Trajectory Optimisation and Reinforcement Learning
Henry Charlesworth, Giovanni Montana
Training agents to autonomously learn how to use anthropomorphic robotic hands has the potential to lead to systems capable of performing a multitude of complex manipulation tasks…
cs.LG2020★ 19 cited
PlanGAN: Model-based Planning With Sparse Rewards and Multiple Goals
Henry Charlesworth, Giovanni Montana
Learning with sparse rewards remains a significant challenge in reinforcement learning (RL), especially when the aim is to train a policy capable of achieving multiple different go…