5 papers
GenSwarm: Scalable Multi-Robot Code-Policy Generation and Deployment via Language Models
Wenkang Ji, Huaben Chen, Mingyang Chen +6
The development of control policies for multi-robot systems traditionally follows a complex and labor-intensive process, often lacking the flexibility to adapt to dynamic tasks. Th…
Multi-Robot Cooperative Herding through Backstepping Control Barrier Functions
Kang Li, Ming Li, Wenkang Ji +2
We propose a novel cooperative herding strategy through backstepping control barrier functions (CBFs), which coordinates multiple herders to herd a group of evaders safely towards…
Multi-Task Multi-Agent Reinforcement Learning via Skill Graphs
Guobin Zhu, Rui Zhou, Wenkang Ji +3
Multi-task multi-agent reinforcement learning (MT-MARL) has recently gained attention for its potential to enhance MARL's adaptability across multiple tasks. However, it is challen…
LAMARL: LLM-Aided Multi-Agent Reinforcement Learning for Cooperative Policy Generation
Guobin Zhu, Rui Zhou, Wenkang Ji +1
Although Multi-Agent Reinforcement Learning (MARL) is effective for complex multi-robot tasks, it suffers from low sample efficiency and requires iterative manual reward tuning. La…
Multi-Agent Consensus Seeking via Large Language Models
Huaben Chen, Wenkang Ji, Lufeng Xu +1
Multi-agent systems driven by large language models (LLMs) have shown promising abilities for solving complex tasks in a collaborative manner. This work considers a fundamental pro…