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Searched for: 1 subject found.
6.7940 Dynamic Programming and Reinforcement Learning
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Not offered regularly; consult department
Prereq: 6.3700 or 18.600
Units: 4-0-8
Dynamic programming as a unifying framework for sequential decision-making under uncertainty, Markov decision problems, and stochastic control. Perfect and imperfect state information models. Finite horizon and infinite horizon problems, including discounted and average cost formulations. Value and policy iteration. Suboptimal methods. Approximate dynamic programming for large-scale problems, and reinforcement learning. Applications and examples drawn from diverse domains. While an analysis prerequisite is not required, mathematical maturity is necessary.
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