"Reinforcement learning has historical roots in animal learning and trial-and-error psychology, alongside mathematical developments in optimal control and dynamic programming."
Sutton and Barto describe reinforcement learning as learning through interaction with an environment and feedback from rewards. Their historical account identifies animal-learning psychology, optimal control, and temporal-difference learning as major intellectual foundations, showing how reinforcement learning brings together behavioural and engineering traditions.
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