GATSBY COMPUTATIONAL NEUROSCIENCE UNIT
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Bert Kappen

Radboud University Nijmegen, the Netherlands

 

Thursday 27 March 2008

 

16.00

 

4th Floor Seminar Room, Alexandra House

 

An efficient approach to stochastic optimal control

 

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.