most citedMASQ: Multi-Agent Reinforcement Learning for Single Quadruped Robot Locomotion

1 citations · 1 across the 2 of their papers we have counts for

collaborators

2 papers

cs.RO2024★ 1 cited

MASQ: Multi-Agent Reinforcement Learning for Single Quadruped Robot Locomotion

Qi Liu, Jingxiang Guo, Sixu Lin +3

This paper proposes a novel method to improve locomotion learning for a single quadruped robot using multi-agent deep reinforcement learning (MARL). Many existing methods use singl…

cs.AI2024

Multi-Agent Target Assignment and Path Finding for Intelligent Warehouse: A Cooperative Multi-Agent Deep Reinforcement Learning Perspective

Qi Liu, Jianqi Gao, Dongjie Zhu +4

Multi-agent target assignment and path planning (TAPF) are two key problems in intelligent warehouse. However, most literature only addresses one of these two problems separately.…