随机博弈的边际值

IF 1.4 3区 数学 Q2 MATHEMATICS, APPLIED Mathematics of Operations Research Pub Date : 2024-03-12 DOI:10.1287/moor.2023.0297
Luc Attia, Miquel Oliu-Barton, Raimundo Saona
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引用次数: 0

摘要

零和随机博弈的参数包括报酬、转换和可能的贴现率。在本文中,我们将研究当这些参数受到扰动时,主要的解概念(贴现值和未贴现值)是如何变化的。我们重点研究米尔斯于 1956 年在矩阵博弈中引入的边际值--即沿着任何固定扰动的值的方向导数。我们提供了贴现随机博弈的边际值公式。此外,根据对扰动的温和假设,我们还给出了贴现率消失时的极限值公式,以及未贴现随机博弈的边际值公式。我们还通过一个例子说明,后两者在一般情况下是不同的:本研究得到了 Fondation CFM pour la Recherche、欧洲研究理事会 [Grant ERC-CoG-863818 (ForM-SMArt)] 和 Agence Nationale de la Recherche [Grant ANR-21-CE40-0020] 的支持。
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Marginal Values of a Stochastic Game
Zero-sum stochastic games are parameterized by payoffs, transitions, and possibly a discount rate. In this article, we study how the main solution concepts, the discounted and undiscounted values, vary when these parameters are perturbed. We focus on the marginal values, introduced by Mills in 1956 in the context of matrix games—that is, the directional derivatives of the value along any fixed perturbation. We provide a formula for the marginal values of a discounted stochastic game. Further, under mild assumptions on the perturbation, we provide a formula for their limit as the discount rate vanishes and for the marginal values of an undiscounted stochastic game. We also show, via an example, that the two latter differ in general.Funding: This work was supported by Fondation CFM pour la Recherche; the European Research Council [Grant ERC-CoG-863818 (ForM-SMArt)]; and Agence Nationale de la Recherche [Grant ANR-21-CE40-0020].
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来源期刊
Mathematics of Operations Research
Mathematics of Operations Research 管理科学-应用数学
CiteScore
3.40
自引率
5.90%
发文量
178
审稿时长
15.0 months
期刊介绍: Mathematics of Operations Research is an international journal of the Institute for Operations Research and the Management Sciences (INFORMS). The journal invites articles concerned with the mathematical and computational foundations in the areas of continuous, discrete, and stochastic optimization; mathematical programming; dynamic programming; stochastic processes; stochastic models; simulation methodology; control and adaptation; networks; game theory; and decision theory. Also sought are contributions to learning theory and machine learning that have special relevance to decision making, operations research, and management science. The emphasis is on originality, quality, and importance; correctness alone is not sufficient. Significant developments in operations research and management science not having substantial mathematical interest should be directed to other journals such as Management Science or Operations Research.
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