Dynamic Programming and Reinforcement Learning

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1500

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(CASMA 381 OR ENGEK 500 OR ENGME 308) and ENGEC 402, ENGEC 501 or ENGME 510 - Introduction to sequential decision making via dynamic programming. The principle of optimality as a unified approach to optimal control of dynamic systems and Markovian decision problems. Applications from control theory and operations research include linear-quadratic problems, the discrete Kalman Filter, inventory control, network, investment, and resource allocation models. Adaptive control and numerical solutions through successive approximation and policy iteration, suboptimal control, and neural network applications involving functional approximations and learning. Same as ENGEC 710 and ENGME 710. Students may not receive credits for both→ENG SE 710→unlocks 0 courses

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