7 citations · 7 across the 1 of their papers we have counts for
3 papers
cs.LG2021★ 7 cited
Off-Policy Imitation Learning from Observations
Zhuangdi Zhu, Kaixiang Lin, Bo Dai +1
Learning from Observations (LfO) is a practical reinforcement learning scenario from which many applications can benefit through the reuse of incomplete resources. Compared to conv…
cs.LG2020
Learning Sparse Rewarded Tasks from Sub-Optimal Demonstrations
Zhuangdi Zhu, Kaixiang Lin, Bo Dai +1
Model-free deep reinforcement learning (RL) has demonstrated its superiority on many complex sequential decision-making problems. However, heavy dependence on dense rewards and hig…
cs.MA2018
Efficient Collaborative Multi-Agent Deep Reinforcement Learning for Large-Scale Fleet Management
Kaixiang Lin, Renyu Zhao, Zhe Xu +1
Large-scale online ride-sharing platforms have substantially transformed our lives by reallocating transportation resources to alleviate traffic congestion and promote transportati…