4 citations · 6 across the 7 of their papers we have counts for
4 papers · 1 filter
Spatio-Temporal Transformer-Based Reinforcement Learning for Robot Crowd Navigation
Haodong He, Hao Fu, Qiang Wang +2
The social robot navigation is an open and challenging problem. In existing work, separate modules are used to capture spatial and temporal features, respectively. However, such me…
SVDE: Scalable Value-Decomposition Exploration for Cooperative Multi-Agent Reinforcement Learning
Shuhan Qi, Shuhao Zhang, Qiang Wang +3
Value-decomposition methods, which reduce the difficulty of a multi-agent system by decomposing the joint state-action space into local observation-action spaces, have become popul…
Identifying Expert Behavior in Offline Training Datasets Improves Behavioral Cloning of Robotic Manipulation Policies
Qiang Wang, Robert McCarthy, David Cordova Bulens +4
This paper presents our solution for the Real Robot Challenge (RRC) III, a competition featured in the NeurIPS 2022 Competition Track, aimed at addressing dexterous robotic manipul…
Improving Behavioural Cloning with Positive Unlabeled Learning
Qiang Wang, Robert McCarthy, David Cordova Bulens +6
Learning control policies offline from pre-recorded datasets is a promising avenue for solving challenging real-world problems. However, available datasets are typically of mixed q…