22 citations · 69 across the 13 of their papers we have counts for
5 papers · 1 filter
Measuring Acoustics with Collaborative Multiple Agents
Yinfeng Yu, Changan Chen, Lele Cao +2
As humans, we hear sound every second of our life. The sound we hear is often affected by the acoustics of the environment surrounding us. For example, a spacious hall leads to mor…
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…
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…
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…
On the Semantics of Gringo
Amelia Harrison, Vladimir Lifschitz, Fangkai Yang
Input languages of answer set solvers are based on the mathematically simple concept of a stable model. But many useful constructs available in these languages, including local var…