The recently proposed machine learning algorithm, deep fictitious play, provides a novel and efficient tool for finding Markovian Nash equilibrium of large N - ...

Mar 22, 2019 · Abstract:In this paper, we apply the idea of fictitious play to design deep neural networks (DNNs), and develop deep learning theory and ...

Aug 12, 2020 · In this paper, we prove the convergence of deep fictitious play (DFP) to the true Nash equilibrium. We can also show that the strategy based on ...

Convergence of deep fictitious play for stochastic differential games. Jiequn Han 1,2, ,; Ruimeng Hu 3, , and; Jihao Long 4. 1. Center for Computational ...

In Section 3, we apply deep fictitious play to linear quadratic games, and prove the convergence of fictitious play under proper assumptions on parameters, with ...

In this talk, I will focus on the convergence analysis for deep fictitious play, which is a novel machine learning algorithm for ... player asymmetric stochastic ...

Sep 29, 2020 · The recently proposed machine learning algorithm, deep fictitious play, provides a novel efficient tool for finding Markovian Nash equilibrium ...

The idea of fictitious play is applied to design deep neural networks (DNNs), and deep learning theory and algorithms for computing the Nash equilibrium of ...

In this paper, we prove the convergence of deep fictitious play (DFP) to the true Nash equilibrium. We can also show that the strategy based on DFP forms an $\ ...

The recently proposed machine learning algorithm, deep fictitious play, provides a novel efficient tool for finding Markovian Nash equilibrium of large $N$- ...