Université Paris-Est Université Paris-Est - Marne-la-Vallée Université Paris-Est - Créteil Val-de-Marne Centre National de la Recherche Scientifique

Probabilistic numerical approximation for stochastic control problems

Site: 
Date: 
01/06/2012 - 15:00
Salle: 
3B 075
Orateur: 
TAN Xiaolu
Localisation: 
École polytechnique
Localisation: 
France
Résumé: 

We give a probabilistic interpretation of the Monte-Carlo scheme proposed by Fahim, Touzi and Warin for fully nonlinear parabolic PDEs, and hence generalize it to the non-Markovian case for a general stochastic control problem. General convergence result is obtained by weak convergence method as in Kushner. We also get a rate of convergence using the invariance principle technique as in Dolinsky's work, which is better than that obtained by viscosity solution method.