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Reinforcement Learning and Dynamic Programming Using Function Approximators

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From household appliances to applications in robotics, engineered systems involving complex dynamics can only be as effective as the algorithms that control them. While Dynamic Programming (DP) has provided researchers with a way to optimally solv

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