2 papers
cs.LG2025
Sample-Efficient Policy Constraint Offline Deep Reinforcement Learning based on Sample Filtering
Yuanhao Chen, Qi Liu, Pengbin Chen +2
Offline reinforcement learning (RL) aims to learn a policy that maximizes the expected return using a given static dataset of transitions. However, offline RL faces the distributio…
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.…