Multi-agent reinforcement learning

Multi-agent reinforcement learning is a type of artificial intelligence where multiple computer agents work together to solve problems. It works by having each agent learn from its own experiences, such as taking an action in an environment and receiving feedback from it. When each agent is faced with a problem, it must decide what action to take in order for the group to achieve the best possible outcome. By working together, the agents can quickly and efficiently achieve the goal.