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cs.AI2022
Advice Conformance Verification by Reinforcement Learning agents for Human-in-the-Loop
Mudit Verma, Ayush Kharkwal, Subbarao Kambhampati
Human-in-the-loop (HiL) reinforcement learning is gaining traction in domains with large action and state spaces, and sparse rewards by allowing the agent to take advice from HiL.…
cs.AI2022
Towards customizable reinforcement learning agents: Enabling preference specification through online vocabulary expansion
Utkarsh Soni, Nupur Thakur, Sarath Sreedharan +4
There is a growing interest in developing automated agents that can work alongside humans. In addition to completing the assigned task, such an agent will undoubtedly be expected t…