Speaker: Bert Kappen (Donder Institute, Radboud University, Netherlands)
Stochastic optimal control theory deals with the problem to compute an optimal set of actions to attain some future goal. Examples are found in many contexts such as motor control tasks for robotics, planning and scheduling tasks or managing a financial portfolio.
The computation of the optimal control is typically very difficult due to the size of the state space and the stochastic nature of the problem. For a special class of non-linear stochastic control problems, the solution can be mapped onto a statistical inference problem. For these so-called path integral control problems the optimal cost-to-go solution of the Bellman equation is given by the minimum of a free energy.
I will give a high level introduction to the underlying theory and illustrate with some examples from robotics and other areas.
Sandwich lunch available from 12.30pm, seminar starts at 1.00pm.
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When and where
1.00pm - 2.00pmWednesday 23rd October 2019