Task Decoupling in Preference-based Reinforcement Learning for Personalized Human-Robot Interaction
Mingjiang Liu,Chunlin Chen,Mingjiang Liu,Chunlin Chen
Intelligent robots designed to interact with hu-mans in the real world need to adapt to the preferences of different individuals. Preference-based reinforcement learning (RL) has shown great potential for teaching robots to learn personalized behaviors from interacting with humans with-out a meticulous, hand-crafted reward function, replaced by learning reward based on a human's preferences betwee...
