22 citations · 29 across the 7 of their papers we have counts for
12 papers
Greedy based Value Representation for Optimal Coordination in Multi-agent Reinforcement Learning
Lipeng Wan, Zeyang Liu, Xingyu Chen +2
Due to the representation limitation of the joint Q value function, multi-agent reinforcement learning methods with linear value decomposition (LVD) or monotonic value decompositio…
Robotic Grasping from Classical to Modern: A Survey
Hanbo Zhang, Jian Tang, Shiguang Sun +1
Robotic Grasping has always been an active topic in robotics since grasping is one of the fundamental but most challenging skills of robots. It demands the coordination of robotic…
Density-based Curriculum for Multi-goal Reinforcement Learning with Sparse Rewards
Deyu Yang, Hanbo Zhang, Xuguang Lan +1
Multi-goal reinforcement learning (RL) aims to qualify the agent to accomplish multi-goal tasks, which is of great importance in learning scalable robotic manipulation skills. Howe…
MBDF-Net: Multi-Branch Deep Fusion Network for 3D Object Detection
Xun Tan, Xingyu Chen, Guowei Zhang +2
Point clouds and images could provide complementary information when representing 3D objects. Fusing the two kinds of data usually helps to improve the detection results. However,…
Probabilistic Human Motion Prediction via A Bayesian Neural Network
Jie Xu, Xingyu Chen, Xuguang Lan +1
Human motion prediction is an important and challenging topic that has promising prospects in efficient and safe human-robot-interaction systems. Currently, the majority of the hum…
Multi-agent Policy Optimization with Approximatively Synchronous Advantage Estimation
Lipeng Wan, Xuwei Song, Xuguang Lan +1
Cooperative multi-agent tasks require agents to deduce their own contributions with shared global rewards, known as the challenge of credit assignment. General methods for policy b…