6.231 Dynamic Programming and Stochastic Control, Fall 2008
Name
6-231-fall-2008/contents/index.htm
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28.29 KB
Format
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Checksum (MD5)
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Author(s)
Bertsekas, Dimitri
Alternative Title
Dynamic Programming and Stochastic Control
Date Issued
December 2008
Abstract
This 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 (finite and infinite horizon). We will also discuss some 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
decision making
uncertainty
sequential decision making
finite horizon
infinite horizon
approximation methods
state space
large state space
optimal control
dynamical system
dynamic programming and optimal control
deterministic systems
shortest path
state information
rollout
stochastic shortest path
approximate dynamic programming
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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