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Reinforcement learning is a type of machine learning that focuses on training AI agents to interact with an environment, learn from feedback, and make decisions to maximize rewards. It revolves around the concept of an agent interacting with an environment, taking action based on its current state and the feedback it receives, and adjusting behavior accordingly. The agent’s goal is to maximize the cumulative rewards over time by selecting actions based on its current state and policy.
