Stability of backward inverse problems for degenerate mean-field game systems

TL;DR

This paper establishes stability estimates for inverse backward problems in degenerate mean-field game systems, enabling the determination of intermediate states from final data using Carleman estimates.

Contribution

It introduces a novel approach applying Carleman estimates to degenerate MFG systems for stability analysis of inverse problems.

Findings

Proved Carleman estimate for HJB equation

Derived Carleman estimate for Fokker-Planck equation

Established conditional stability for backward inverse problems

Abstract

We investigate inverse backward-in-time problems for a class of second-order degenerate Mean-Field Game (MFG) systems. More precisely, given the final datum $(u(\cdot, T),m(\cdot, T))$ of a solution to the one-dimensional mean-field game system with a degenerate diffusion coefficient, we aim to determine the intermediate states $(u(\cdot,t_{0}),m(\cdot,t_{0}))$ for any $t_{0} \in [0, T)$, i.e., the value function and the mean distribution at intermediate times, respectively. We prove conditional stability estimates under suitable assumptions on the diffusion coefficient and the initial state $(u(\cdot,0),m(\cdot,0))$. The proofs are based on Carleman's estimates with a simple weight function. We first prove a Carleman estimate for the Hamilton-Jacobi-Bellman (HJB) equation. A second Carleman estimate will be derived for the Fokker-Planck (FP) equation. Then, by combining the two estimates, we obtain a Carleman estimate for the mean-field game system, leading to the stability of the backward problems.