In recent years, multi-agent reinforcement learning (MARL) has presented impressive performance in various applications. However, physical limitations, budget restrictions, and many other factors usually impose constraints on a system (MAS), which cannot be handled by traditional MARL frameworks. Specifically, this paper focuses constrained MASes where agents work cooperatively to maximize the ...