Tipo di tesi
Tesi di laurea magistrale
Titolo
A study on the connection between Mean Field Games and Generative Adversarial Network
Corso di studi
MATEMATICA
Parole chiave
- generative adversarial networks
- mean field games
Data inizio appello
23/09/2022
Consultabilità
Tesi non consultabile
Riassunto (Italiano)
We analyse the connection between Mean Field Games (MFGs) and a popular Machine Learning model, namely Generative Adversarial Networks (GANs). From the game theoretical perspective, GANs can be interpreted as MFGs under Pareto Optimality condition. On the other side, we take advantage of the adversarial nature of GANs in order to numerically approximate Mean Field Equilibria, which are expressed as solutions of a system of coupled PDEs: a forward Fokker-Plank equation and a backward Hamilton-Jacobi-Bellman equation.
