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Reinforcement learning (RL) is a method of machine learning that uses trial and error to improve an AI model’s capabilities. It is used in systems that make sequential decisions, such as playing games, and has been successfully applied to games like poker and Go. RL allows AI models to learn from their own mistakes and optimize for rewards.