most citedExploiting Transformer in Sparse Reward Reinforcement Learning for Interpretable Temporal Logic Motion Planning

14 citations · 14 across the 1 of their papers we have counts for

collaborators

1 paper

cs.RO2022★ 14 cited

Exploiting Transformer in Sparse Reward Reinforcement Learning for Interpretable Temporal Logic Motion Planning

Hao Zhang, Hao Wang, Zhen Kan

Automaton based approaches have enabled robots to perform various complex tasks. However, most existing automaton based algorithms highly rely on the manually customized representa…