Reinforcement Learning: AI agents that learn through trial and error by interacting with an environment

Reinforcement Learning (RL) is a subfield of Artificial Intelligence (AI) that focuses on developing intelligent agents capable of learning and making decisions by interacting with an environment. RL agents learn through a process of trial and error, where they receive feedback in the form of rewards or penalties based on their actions. Over time, they optimize their behavior to maximize the cumulative reward obtained from the environment. Here are some key aspects of reinforcement learning:

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