A multi-agent AI system is a computational framework composed of multiple autonomous or semi-autonomous intelligent agents that interact within a shared environment to achieve individual or collective goals.

These agents can perceive their surroundings, make decisions, and take actions independently, but they may also cooperate, coordinate, compete, or negotiate with one another. Each agent typically has its own capabilities, knowledge, and objectives, and the system’s overall behavior emerges from their interactions rather than being centrally controlled.

Multi-agent AI systems are used to model complex, distributed, or dynamic problems where a single agent would be insufficient—such as simulations, robotics, supply chains, financial markets, and large-scale digital platforms. They often incorporate elements of machine learning, game theory, and distributed computing to enable adaptive and scalable behavior.