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cs.RO2026
Temporal Logic Guided Universal Task Representations for Reinforcement Learning
Hao Zhang, Zhangli Zhou, Zhen Kan
Task guided agents demonstrate strong performance in a wide range of complex tasks. However, most existing task representation algorithms are tailored to specific contexts and stru…
cs.RO2024
Exploiting Hybrid Policy in Reinforcement Learning for Interpretable Temporal Logic Manipulation
Hao Zhang, Hao Wang, Xiucai Huang +2
Reinforcement Learning (RL) based methods have been increasingly explored for robot learning. However, RL based methods often suffer from low sampling efficiency in the exploration…