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A multi-agent system (MAS) is a computational system composed of multiple autonomous agents that interact with each other and their environment to achieve specific goals. Each agent in a MAS is capable of perceiving its environment, making decisions, and taking actions. These agents can be software programs or physical robots. MAS is used in various domains, including artificial intelligence, robotics, economics, and social sciences. It allows for decentralized decision-making and coordination among agents, enabling them to work together towards a common objective or to solve complex problems that are difficult for a single agent to handle. In a MAS, agents can communicate with each other through message passing, exchange information, negotiate, and coordinate their actions. They can also learn from their interactions and adapt their behavior over time. The interactions among agents can be cooperative, competitive, or a combination of both, depending on the specific goals and tasks of the MAS. MAS has applications in various fields, such as traffic management, supply chain optimization, swarm robotics, and online auctions. It offers advantages such as scalability, fault tolerance, and flexibility, as the system can adapt and reconfigure itself based on changing conditions or agent failures. Overall, a multi-agent system is a powerful tool for modeling and solving complex problems that involve multiple interacting entities, and it has
