Reinforcement learning

 Reinforcement learning is a type of machine learning where an AI agents learn to make decisions and optimize their behavior through trial and error, based on feedback from the environment. It involves rewarding desired actions and punishing undesired actions to guide the agent towards the best possible outcome. This method is often used in game-playing AI, robotics, and decision-making systems.

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