6.231 Dynamic Programming and Stochastic Control, Fall 2011
Name
6-231-fall-2011/contents/index.htm
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Checksum (MD5)
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Author(s)
Bertsekas, Dimitri
Alternative Title
Dynamic Programming and Stochastic Control
Date Issued
December 2011
Abstract
The course covers the basic models and solution techniques for problems of sequential decision making under uncertainty (stochastic control). We will consider optimal control of a dynamical system over both a finite and an infinite number of stages. This includes systems with finite or infinite state spaces, as well as perfectly or imperfectly observed systems. We will also discuss approximation methods for problems involving large state spaces. Applications of dynamic programming in a variety of fields will be covered in recitations.
Subjects
dynamic programming
stochastic control
algorithms
finite-state
continuous-time
imperfect state information
suboptimal control
finite horizon
infinite horizon
discounted problems
stochastic shortest path
approximate dynamic programming
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
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