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Learning algorithms

24 bytes added, 24 April
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===[[Reinforcement Learning]]===
Reinforcement Learning involves agents learning to make decisions by interacting with an environment to maximize cumulative rewards. It's foundational in fields where sequential decision-making is crucial, like gaming, autonomous vehicles, and robotics. RL uses methods like Q-learning and policy gradient to iteratively improve agent performance based on feedback from the environment.
 
[[Category: Software]]

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