Multi-agent reinforcement learning (MARL) has enjoyed significant recent...
Task allocation can enable effective coordination of multi-robot teams t...
Effective close-proximity human-robot interaction (CP-HRI) requires robo...
Task allocation in heterogeneous multi-agent teams often requires reason...
Existing learning approaches to dexterous manipulation use demonstration...
Complex, multi-objective missions require the coordination of heterogene...
Imitation learning is a promising approach to help robots acquire dexter...
To realize effective heterogeneous multi-robot teams, researchers must
l...
Existing approaches to coalition formation often assume that requirement...
Multi-robot task allocation (MRTA) problems involve optimizing the alloc...
We address the problem of adapting robot trajectories to improve safety,...
Robot task execution when situated in real-world environments is fragile...
In this paper we present a technique for learning how to solve a multi-r...
We propose a learning framework, named Multi-Coordinate Cost Balancing
(...
Large teams of robots have the potential to solve complex multi-task pro...