3 papers
cs.AI2026
HiComm: Hierarchical Communication for Multi-agent Reinforcement Learning
Runze Zhao, Dongruo Zhou, Sumit Kumar Jha +2
Cooperative multi-agent reinforcement learning (MARL) often relies on communication to mitigate partial observability, yet most existing protocols treat messages as flat dense vect…
cs.LG2025
Instance-Dependent Continuous-Time Reinforcement Learning via Maximum Likelihood Estimation
Runze Zhao, Yue Yu, Ruhan Wang +2
Continuous-time reinforcement learning (CTRL) provides a natural framework for sequential decision-making in dynamic environments where interactions evolve continuously over time.…
cs.LG2025
Sample and Computationally Efficient Continuous-Time Reinforcement Learning with General Function Approximation
Runze Zhao, Yue Yu, Adams Yiyue Zhu +2
Continuous-time reinforcement learning (CTRL) provides a principled framework for sequential decision-making in environments where interactions evolve continuously over time. Despi…