1 citations · 1 across the 4 of their papers we have counts for
4 papers
Learning to Advise and Learning from Advice in Cooperative Multi-Agent Reinforcement Learning
Yue Jin, Shuangqing Wei, Jian Yuan +1
Learning to coordinate is a daunting problem in multi-agent reinforcement learning (MARL). Previous works have explored it from many facets, including cognition between agents, cre…
Information-Bottleneck-Based Behavior Representation Learning for Multi-agent Reinforcement learning
Yue Jin, Shuangqing Wei, Jian Yuan +1
In multi-agent deep reinforcement learning, extracting sufficient and compact information of other agents is critical to attain efficient convergence and scalability of an algorith…
Supervised Off-Policy Ranking
Yue Jin, Yue Zhang, Tao Qin +4
Off-policy evaluation (OPE) is to evaluate a target policy with data generated by other policies. Most previous OPE methods focus on precisely estimating the true performance of a…
Balancing Exploration for Online Receding Horizon Learning Control with Provable Regret Guarantees
Deepan Muthirayan, Jianjun Yuan, Pramod P. Khargonekar
We address the problem of simultaneously learning and control in an online receding horizon control setting. We consider the control of an unknown linear dynamical system with gene…