A multi-agent system (MAS) is a sophisticated computational paradigm where several autonomous, interacting entities, known as agents, work together to achieve common or individual objectives. Each agent typically possesses its own perceptions, decision-making capabilities, and actions, operating within a shared environment. The core mechanism involves these agents communicating, cooperating, or even competing to solve problems that are too complex or distributed for a single agent to handle. This approach is crucial for achieving scalable, efficient, and collaborative solutions, particularly in scenarios requiring diverse functionalities or distributed processing. For instance, an LLM-driven multi-agent controller can coordinate vision, dialogue, and state management agents for personalized nutrition [2601.04491v1]. MAS frameworks are increasingly adopted in fields like Embodied AI, robotics, and personalized health, where they enable advanced human-agent interactions and enhance system efficiency through intelligent task delegation [2601.18733v1].
Multi-agent systems are like teams of specialized AI programs or robots that work together to solve complex problems more effectively. By coordinating their actions and delegating tasks, they achieve scalable and efficient solutions that a single AI could not manage alone.
MAS, multi-agent framework, distributed AI, agent-based system
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