English

Finite-Agent Stochastic Differential Games on Large Graphs: I. The Linear-Quadratic Case

Optimization and Control 2025-11-19 v3

Abstract

In this paper, we study finite-agent linear-quadratic games on graphs. Specifically, we propose a comprehensive framework that extends the existing literature by incorporating heterogeneous and interpretable player interactions. Compared to previous works, our model offers a more realistic depiction of strategic decision-making processes. For general graphs, we establish the convergence of fictitious play, a widely-used iterative solution method for determining the Nash equilibrium of our proposed game model. Notably, under appropriate conditions, this convergence holds true irrespective of the number of players involved. For vertex-transitive graphs, we develop a semi-explicit characterization of the Nash equilibrium. Through rigorous analysis, we demonstrate the well-posedness of this characterization under certain conditions. We present numerical experiments that validate our theoretical results and provide insights into the intricate relationship between various game dynamics and the underlying graph structure.

Keywords

Cite

@article{arxiv.2406.09523,
  title  = {Finite-Agent Stochastic Differential Games on Large Graphs: I. The Linear-Quadratic Case},
  author = {Ruimeng Hu and Jihao Long and Haosheng Zhou},
  journal= {arXiv preprint arXiv:2406.09523},
  year   = {2025}
}

Comments

Code available at https://github.com/Haosheng-Zhou/Finite-Agent-Stochastic-Differential-Games-on-Large-Graphs-The-Linear-Quadratic-Case

R2 v1 2026-06-28T17:05:13.090Z