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cs.AI2019
A Human-Centered Data-Driven Planner-Actor-Critic Architecture via Logic Programming
Daoming Lyu, Fangkai Yang, Bo Liu +1
Recent successes of Reinforcement Learning (RL) allow an agent to learn policies that surpass human experts but suffers from being time-hungry and data-hungry. By contrast, human l…
cs.AI2019
A Joint Planning and Learning Framework for Human-Aided Decision-Making
Daoming Lyu, Fangkai Yang, Bo Liu +1
Conventional reinforcement learning (RL) allows an agent to learn policies via environmental rewards only, with a long and slow learning curve, especially at the beginning stage. O…
cs.AI2018
SDRL: Interpretable and Data-efficient Deep Reinforcement Learning Leveraging Symbolic Planning
Daoming Lyu, Fangkai Yang, Bo Liu +1
Deep reinforcement learning (DRL) has gained great success by learning directly from high-dimensional sensory inputs, yet is notorious for the lack of interpretability. Interpretab…