Multi-Agent Systems
Multi-Agent Systems (MAS) are computational frameworks where multiple autonomous agents interact within an environment to achieve individual or collective goals. These agents can be software entities, robots, or AI systems that perceive their surroundings, make decisions, and act based on rules or learning algorithms. MAS is used to model complex systems like traffic networks, economic markets, or distributed AI applications, enabling emergent behaviors and decentralized problem-solving.
Developers should learn MAS when building distributed, scalable, or collaborative systems, such as in robotics, IoT networks, or AI simulations where centralized control is impractical. It's essential for applications requiring autonomous decision-making, coordination, or negotiation among components, like in smart grids, autonomous vehicles, or multi-player game AI. MAS provides a robust paradigm for handling uncertainty, adaptability, and resource allocation in dynamic environments.