English

Infinite dimensional weak Dirichlet processes, stochastic PDEs and optimal control

Probability 2016-06-14 v2

Abstract

The present paper continues the study of infinite dimensional calculus via regularization, started by C. Di Girolami and the second named author, introducing the notion of "weak Dirichlet process" in this context. Such a process \X\X, taking values in a Hilbert space HH, is the sum of a local martingale and a suitable "orthogonal" process. The new concept is shown to be useful in several contexts and directions. On one side, the mentioned decomposition appears to be a substitute of an It\^o type formula applied to f(t,\X(t))f(t, \X(t)) where f:[0,T]×HRf:[0,T] \times H \rightarrow \R is a C0,1C^{0,1} function and, on the other side, the idea of weak Dirichlet process fits the widely used notion of "mild solution" for stochastic PDE. As a specific application, we provide a verification theorem for stochastic optimal control problems whose state equation is an infinite dimensional stochastic evolution equation.

Keywords

Cite

@article{arxiv.1207.5710,
  title  = {Infinite dimensional weak Dirichlet processes, stochastic PDEs and optimal control},
  author = {Giorgio Fabbri and Francesco Russo},
  journal= {arXiv preprint arXiv:1207.5710},
  year   = {2016}
}
R2 v1 2026-06-21T21:40:41.761Z