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SDEs and MFGs towards Machine Learning applications

We present results that span three interconnected domains. Initially, our analysis is centred on Backward Stochastic Differential Equations (BSDEs) featuring time-delayed generators. Subsequently, we direct our interest towards Mean Field Games (MFGs) incorporating absorption aspects, with a focus on the corresponding Master Equation within a confined domain under the imposition of Dirichlet boundary conditions. The investigation culminates in exploring pertinent Machine Learning methodologies applied to financial and economic decision-making processes.

Identiferoai:union.ndltd.org:unitn.it/oai:iris.unitn.it:11572/398234
Date04 December 2023
CreatorsGarbelli, Matteo
ContributorsGarbelli, Matteo, Di Persio, Luca
PublisherUniversità degli studi di Trento, place:TRENTO
Source SetsUniversità di Trento
LanguageEnglish
Detected LanguageEnglish
Typeinfo:eu-repo/semantics/doctoralThesis
Rightsinfo:eu-repo/semantics/openAccess
Relationfirstpage:1, lastpage:203, numberofpages:203

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