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arXiv 2602.19210math.PRmath.OC
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粗糙公共噪声下的平均场博弈:线性二次情形

Mean-field games with rough common noise: the linear-quadratic case

Technische Universität Berlin(柏林工业大学);Weierstraß-Institut(韦伊尔斯特拉斯研究所);Humboldt Universität zu Berlin(柏林洪堡大学)

Peter K. Friz, Ioannis Gasteratos, Ulrich Horst, Stefanos Theodorakopoulos

AI总结:

针对粗糙公共噪声的线性二次平均场博弈,提出Volterra型公式化方法,通过粗糙正倒向随机微分方程刻画最优状态与控制,证明存在唯一性及稳定性。

摘要:

受具有公共噪声的平均场博弈(MFG)和路径随机控制理论的启发,我们在此公式化了具有粗糙公共噪声的线性二次(LQ)MFG,并给出了线性二次情形的良好适定性理论。一种新颖的Volterra型(或温和)公式化方法使得技术性(粗糙-随机)考虑降至最低。我们通过粗糙正倒向随机微分方程(粗糙FBSDE)推导出最优状态和最优控制的刻画,并在通常假设下提供了存在唯一性结果。我们的理论伴随着关于初始数据和公共噪声的稳定性估计,同时我们还建立了所谓的粗糙平均场博弈的Itô-Lions-Lyons映射的连续性。最后,我们讨论了在系数适当条件下粗糙公共噪声的随机化。当后者由与异质噪声独立的布朗运动的Stratonovich提升给定时,我们证明粗糙LQ MFG的解与通过条件化公共噪声得到的解一致。

英文摘要:

Motivated by mean-field games (MFG) with common noise on the one hand and pathwise stochastic control theory on the other, we formulate here a linear-quadratic (LQ) MFG with rough common noise, along with a satisfactory well-posedness theory for the linear-quadratic case. A novel Volterra-type (or mild) formulation allows to keep technical (rough-stochastic) consideration to a minimum. We derive a characterization of the optimal state and optimal control through a rough forward-backward SDE (rough FBSDE), and provide an existence and uniqueness result under the usual assumptions. Our theory is accompanied by stability estimates with respect to initial data and common noise while we also establish continuity of what we call the Itô-Lions-Lyons map for rough mean-field games. Finally, we discuss randomization of the rough common noise under appropriate conditions on the coefficients. When the latter is given by the Stratonovich lift of a Brownian motion independent of the idiosyncratic noise, we show that solutions of the rough LQ MFG coincide with those obtained by conditioning on the common noise.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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