BEGIN:VCALENDAR VERSION:2.0 PRODID:researchseminars.org CALSCALE:GREGORIAN X-WR-CALNAME:researchseminars.org BEGIN:VEVENT SUMMARY:Hilbert Johan Kappen (Donder Institute\, Radboud University Nijmeg en\, the Netherlands) DTSTART:20200528T163000Z DTEND:20200528T173000Z DTSTAMP:20260423T003258Z UID:MPML/7 DESCRIPTION:Title: Pat h integral control theory\nby Hilbert Johan Kappen (Donder Institute\, Radboud University Nijmegen\, the Netherlands) as part of Mathematics\, P hysics and Machine Learning (IST\, Lisbon)\n\n\nAbstract\nStochastic optim al control theory deals with the problem to compute an optimal set of acti ons to attain some future goal. Examples are found in many contexts such a s motor control tasks for robotics\, planning and scheduling tasks or mana ging a financial portfolio. The computation of the optimal control is typi cally very difficult due to the size of the state space and the stochastic nature of the problem. Special cases for which the computation is tractab le are linear dynamical systems with quadratic cost and deterministic cont rol problems. For a special class of non-linear stochastic control problem s\, the solution can be mapped onto a statistical inference problem. For t hese so-called path integral control problems the optimal cost-to-go solut ion of the Bellman equation is given by the minimum of a free energy. I wi ll give a high level introduction to the underlying theory and illustrate with some examples from robotics and other areas.\n LOCATION:https://researchseminars.org/talk/MPML/7/ END:VEVENT END:VCALENDAR