What is Reinforcement Learning?

Reinforcement Learning

Definition A machine learning paradigm where an agent learns by taking actions in an environment and receiving reward or penalty signals based on the outcomes. Over many iterations the agent develops a policy that maximizes cumulative reward.

In Depth

Unlike supervised learning, RL does not require labeled input-output pairs; it discovers effective strategies through trial and error. RL has achieved superhuman performance in games like Go and chess and is used in robotics, recommendation systems, and LLM alignment. The core challenge is designing a reward function that truly captures the desired behavior.

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