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Reinforcement Learning and Dynamic Programming Using Function Approximators From household appliances to applications in robotics, engineered systems involving complex dynamics can only be as effective as the algorithms that control them. This title provides a comprehensive exploration of the field of Dynamic Programming (DP) and Reinforcement Learning (RL).
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Dynamic Programming An introduction to the mathematical theory of multistage decision processes, this text takes a “functional equation” approach to the discovery of optimum policies. The text examines existence and uniqueness theorems, the optimal inventory equation, bottleneck problems in multistage production processes, a new formalism in the calculus of variation, multistage games, and more. 1957 edition. Include… Full description