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Reinforcement Learning Overview and Examples by attridhruv9 is a document available to read on EtoBox.

Reinforcement learning involves an agent taking actions in an environment to maximize rewards. It differs from supervised learning by learning from trial-and-error interactions rather than example inputs. The agent learns to achieve a goal like reaching a reward or avoiding penalties by trying actions and receiving feedback about the results of those actions.

Author
attridhruv9
Language
EN