An efficient approach to stochastic optimal control
published: Aug. 5, 2008, recorded: May 2008, views: 2267
Report a problem or upload filesIf you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Stochastic optimal control theory is a principled approach to compute optimal actions with delayed rewards. The use of this approach in AI and machine learning has been limited due to the computational intractabilities. In this talk, I introduce a class of control problems where the intractabilities appear as the computation of a partition sum, as in a statistical mechanical system. This opens the possibility to study phase transitions and to apply exisiting approximation methods such as BP and the variational method to optimal control theory. The talk gives a gentle introduction into control theory and illustrates these new phenomena with a number of examples.
Link this pageWould you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !