6.231 Dynamic Programming and Stochastic Control, Fall 2002
Name
6-231Fall-2002/OcwWeb/Electrical-Engineering-and-Computer-Science/6-231Dynamic-Programming-and-Stochastic-ControlFall2002/CourseHome/index.htm
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15.36 KB
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Checksum (MD5)
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Author(s)
Bertsekas, Dimitri P.
Alternative Title
Dynamic Programming and Stochastic Control
Date Issued
December 2002
Abstract
Sequential decision-making via dynamic programming. Unified approach to optimal control of stochastic dynamic systems and Markovian decision problems. Applications in linear-quadratic control, inventory control, and resource allocation models. Optimal decision making under perfect and imperfect state information. Certainty equivalent and open loop-feedback control, and self-tuning controllers. Infinite horizon problems, successive approximation, and policy iteration. Discounted problems, stochastic shortest path problems, and average cost problems. Optimal stopping, scheduling, and control of queues. Approximations and neurodynamic programming. From the course home page: Course Description This course covers the basic models and solution techniques for problems of sequential decision making under uncertainty (stochastic control). Approximation methods for problems involving large state spaces are also presented and discussed.
Subjects
dynamic programming
stochastic control
mathematics
optimization
algorithms
probability
Markov chains
optimal control
Dynamic programming
Stochastic control theory
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
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