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Main Authors: Guo, Xin, Li, Xun, Zhang, Liangquan
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2507.13256
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author Guo, Xin
Li, Xun
Zhang, Liangquan
author_facet Guo, Xin
Li, Xun
Zhang, Liangquan
contents In this paper, we examine a class of $α$-potential stochastic differential games with random coefficients via the backward stochastic differential equations (BSDEs) approach. Specifically, we show that the first and second order linear derivatives of the objective function for each player can be expressed through the corresponding first and second-order adjoint equations, which leads to rigorous estimates for $α$. We illustrate the dependence of $α$ on game characteristics through detailed analysis of linear-quadratic games, and with common noise.
format Preprint
id arxiv_https___arxiv_org_abs_2507_13256
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle BSDE Approach for $α$-Potential Stochastic Differential Games
Guo, Xin
Li, Xun
Zhang, Liangquan
Optimization and Control
Probability
In this paper, we examine a class of $α$-potential stochastic differential games with random coefficients via the backward stochastic differential equations (BSDEs) approach. Specifically, we show that the first and second order linear derivatives of the objective function for each player can be expressed through the corresponding first and second-order adjoint equations, which leads to rigorous estimates for $α$. We illustrate the dependence of $α$ on game characteristics through detailed analysis of linear-quadratic games, and with common noise.
title BSDE Approach for $α$-Potential Stochastic Differential Games
topic Optimization and Control
Probability
url https://arxiv.org/abs/2507.13256