1 citations · 1 across the 4 of their papers we have counts for
4 papers
Interactive Inverse Reinforcement Learning of Interaction Scenarios via Bi-level Optimization
Yue Mao, Shicheng Liu, Siyuan Xu +1
Inverse reinforcement learning (IRL) learns a reward function and a corresponding policy that best fit the demonstration data of an expert. However, in the current IRL setting, the…
Byzantine-resilient federated online learning for Gaussian process regression
Xu Zhang, Zhenyuan Yuan, Minghui Zhu
In this paper, we study Byzantine-resilient federated online learning for Gaussian process regression (GPR). We develop a Byzantine-resilient federated GPR algorithm that allows a…
Meta-Reinforcement Learning with Universal Policy Adaptation: Provable Near-Optimality under All-task Optimum Comparator
Siyuan Xu, Minghui Zhu
Meta-reinforcement learning (Meta-RL) has attracted attention due to its capability to enhance reinforcement learning (RL) algorithms, in terms of data efficiency and generalizabil…
Federated reinforcement learning for robot motion planning with zero-shot generalization
Zhenyuan Yuan, Siyuan Xu, Minghui Zhu
This paper considers the problem of learning a control policy for robot motion planning with zero-shot generalization, i.e., no data collection and policy adaptation is needed when…