Multi Agent Reinforcement Learning

Multi-Agent Reinforcement Learning (MARL) aims to solve complex problems by integrating multiple agents that focus on different subtasks. This approach typically involves two types of multi-agent systems: independent systems and cooperative systems. MARL not only improves the efficiency of task execution but also enhances the robustness and adaptability of the system, offering broad application value.