Reinforcement Learning

Reinforcement learning (RL) differs from supervised learning in not needing labelled input/output pairs be presented, and in not needing sub-optimal actions to be explicitly corrected. Instead the focus is on finding a balance between exploration (of uncharted territory) and exploitation (of current knowledge). Partially supervised RL algorithms can combine the advantages of supervised and RL algorithms.

Source: Reinforcement Learning | Wikipedia

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