Sensitivity Analysis for Network LQG Mean-Field Games: A Graphon Limit Approach

This paper provides the sensitivity analysis of Linear Quadratic Gaussian graphon mean-field games (LQG-GMFG), with a particular focus on how perturbations in initial conditions at different network locations affect system behavior. We quantify the impact of localized perturbations through a L 2 -perturbation metric via graphon spectral decompositions and establish explicit solutions for the perturbation analysis that reveal how network topology influences perturbation propagation patterns. Our theoretical results reveal fundamental connections among network topology, system dynamics, and sensitivity patterns, providing insights for robust network design and control strategies.

Authors

Institutions

Publication Details

Journal
IFAC-PapersOnLine
Published
2025-01-01
DOI
https://doi.org/10.1016/j.ifacol.2025.07.055
Primary Topic
Stochastic processes and financial applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Sensitivity Analysis for Network LQG Mean-Field Games: A Graphon Limit Approach

Peter E. Caines, Shuang Gao, Tao Zhang
IFAC-PapersOnLine
Stochastic processes and financial applications
article

Sensitivity Analysis for Network LQG Mean-Field Games: A Graphon Limit Approach

Peter E. Caines, Shuang Gao, Tao Zhang
article en

Abstract

This paper provides the sensitivity analysis of Linear Quadratic Gaussian graphon mean-field games (LQG-GMFG), with a particular focus on how perturbations in initial conditions at different network locations affect system behavior. We quantify the impact of localized perturbations through a L 2 -perturbation metric via graphon spectral decompositions and establish explicit solutions for the perturbation analysis that reveal how network topology influences perturbation propagation patterns. Our theoretical results reveal fundamental connections among network topology, system dynamics, and sensitivity patterns, providing insights for robust network design and control strategies.

IFAC-PapersOnLineVol. 59(4)
Polytechnique Montréal (CA), McGill University (CA)
Openalex Percentile: Top 74%
Stochastic processes and financial applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Sensitivity Analysis for Network LQG Mean-Field Games: A Graphon Limit Approach — Peter E. Caines, Shuang Gao, et al. · IFAC-PapersOnLine (2025) | TGRS Research Map | TGRS