Multi-Agent Systems
Multi-agent systems refer to a group of autonomous entities, or "agents," that interact with one another to achieve individual or collective goals. Each agent can make decisions based on its environment, communicate with others, and collaborate or compete as needed. These systems are used in various fields, such as robotics, computer simulations, and artificial intelligence, enabling complex tasks to be tackled more efficiently. By coordinating their actions, agents can solve problems, adapt to changes, and exhibit intelligent behaviors, making multi-agent systems a powerful tool for dynamic and decentralized decision-making.
Additional Insights
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Multi-Agent Systems (MAS) are arrangements where multiple autonomous entities, called agents, interact to achieve individual or collective goals. Each agent can perceive its environment, make decisions, and act independently. These systems are commonly found in various fields, such as robotics, traffic management, and simulations, where cooperation or competition among agents can lead to more effective solutions. By working together or negotiating, agents can solve complex problems that a single entity might struggle with, enhancing efficiency and adaptability in dynamic environments.
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Multi-agent systems are collections of independent entities, called agents, that interact and work together to achieve specific goals. Each agent can be a software program, robot, or even a human, often possessing its own knowledge, objectives, and decision-making abilities. These systems are used in various fields, such as robotics, traffic management, and artificial intelligence, to solve complex problems by leveraging cooperation, negotiation, and communication among agents. The collective behavior of the agents can lead to higher efficiency and better outcomes than a single agent could achieve alone.