41 citations · 44 across the 4 of their papers we have counts for
3 papers · 1 filter
Instructional Agents: Reducing Teaching Faculty Workload through Multi-Agent Instructional Design
Huaiyuan Yao, Wanpeng Xu, Justin Turnau +2
Preparing high-quality instructional materials remains a labor-intensive process that often requires extensive coordination among teaching faculty, instructional designers, and tea…
Joint-Local Grounded Action Transformation for Sim-to-Real Transfer in Multi-Agent Traffic Control
Justin Turnau, Longchao Da, Khoa Vo +4
Traffic Signal Control (TSC) is essential for managing urban traffic flow and reducing congestion. Reinforcement Learning (RL) offers an adaptive method for TSC by responding to dy…
A Survey of Sim-to-Real Methods in RL: Progress, Prospects and Challenges with Foundation Models
Longchao Da, Justin Turnau, Thirulogasankar Pranav Kutralingam +3
Deep Reinforcement Learning (RL) has been explored and verified to be effective in solving decision-making tasks in various domains, such as robotics, transportation, recommender s…