What does "MESA" mean?

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MESA stands for a method used in cooperative learning among multiple agents. In this setting, agents work together to solve problems and make decisions. However, these agents often find it hard to figure out the best way to act, especially when rewards are rare.

MESA helps by teaching agents how to better explore their options. It does this by first finding areas where actions lead to higher rewards, based on previous experiences. Then, it creates different strategies for the agents to explore these rewarding areas.

This method has shown to be effective in various situations. For instance, when tested in games that require multiple steps, MESA proved to help agents perform better. Additionally, in tests where rewards were not easy to come by, agents using MESA did significantly better in different environments designed for multiple agents.

Overall, MESA enhances how agents work together and learn, making it easier for them to tackle more difficult tasks.