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http://hdl.handle.net/10397/93872
Title: | Linear-quadratic-Gaussian mean-field-game with partial observation and common noise | Authors: | Bensoussan, A Feng, X Huang, J |
Issue Date: | Mar-2021 | Source: | Mathematical control and related fields, Mar. 2021, v. 11, no. 1, p. 23-46 | Abstract: | This paper considers a class of linear-quadratic-Gaussian (LQG) mean-field games (MFGs) with partial observation structure for individual agents. Unlike other literature, there are some special features in our formu-lation. First, the individual state is driven by some common-noise due to the external factor and the state-average thus becomes a random process instead of a deterministic quantity. Second, the sensor function of individual observation depends on state-average thus the agents are coupled in triple manner: not only in their states and cost functionals, but also through their observation mechanism. The decentralized strategies for individual agents are derived by the Kalman filtering and separation principle. The consistency condition is obtained which is equivalent to the wellposedness of some forward-backward stochastic differential equation (FBSDE) driven by common noise. Finally, the related ɛ-Nash equilibrium property is verified. | Keywords: | Consistency condition Forward-backward stochastic differential equation Kalman filtering Mean-field games Partial observation Ɛ-Nash equilibrium |
Publisher: | American Institute of Mathematical Sciences | Journal: | Mathematical control and related fields | ISSN: | 2156-8472 | EISSN: | 2156-8499 | DOI: | 10.3934/MCRF.2020025 | Rights: | This article has been published in a revised form in Mathematical Control & Related Fields http://dx.doi.org/10.3934/MCRF.2020025. This version is free to download for private research and study only. Not for redistribution, re-sale or use in derivative works. |
Appears in Collections: | Journal/Magazine Article |
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Huang_Linear-Quadratic-Gaussian_Mean-Field-Game_Partial.pdf | Pre-Published version | 569.23 kB | Adobe PDF | View/Open |
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