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Mathematics > Analysis of PDEs

Title: Stochastic solutions to Hamilton-Jacobi-Bellman Dirichlet problems

Authors: David Criens
Abstract: We consider a nonlinear Dirichlet problem on a bounded domain whose Hamiltonian is given by a Hamilton-Jacobi-Bellman operator with merely continuous and bounded coefficients. The objective of this paper is to study the existence question from a stochastic point of view. Using a relaxed control framework, we define a candidate for a viscosity solution. We prove that this stochastic solution satisfies viscosity sub- and supersolution properties and we establish a strong Markov selection principle, which shows that the stochastic solution can be realized through a strong Markov family. Building on the selection principle, we investigate regularity properties of the stochastic solution. For certain elliptic cases, we show that the strong Markov selection is even a Feller selection, which entails the continuity of the stochastic solution.
Subjects: Analysis of PDEs (math.AP); Probability (math.PR)
Cite as: arXiv:2404.17236 [math.AP]
  (or arXiv:2404.17236v1 [math.AP] for this version)

Submission history

From: David Criens [view email]
[v1] Fri, 26 Apr 2024 08:15:46 GMT (26kb)

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