6.231 Dynamic Programming and Stochastic Control, Fall 2008

6.231 Dynamic Programming and Stochastic Control, Fall 2008

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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 discus...

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Bibliographic Details
Main Author: Bertsekas, Dimitri
Other Authors: Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Format: Learning Object
Language:en-US
Published: 2008
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
Online Access:http://hdl.handle.net/1721.1/75813

Internet

http://hdl.handle.net/1721.1/75813

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