Reinforcement learning

Reinforcement learning is a type of machine learning where AI agents learn to make decisions and optimize their behaviour 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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