Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/93874
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Applied Mathematics | en_US |
dc.creator | Xie, T | en_US |
dc.creator | Wang, BC | en_US |
dc.creator | Huang, J | en_US |
dc.date.accessioned | 2022-08-03T01:24:02Z | - |
dc.date.available | 2022-08-03T01:24:02Z | - |
dc.identifier.issn | 1292-8119 | en_US |
dc.identifier.uri | http://hdl.handle.net/10397/93874 | - |
dc.language.iso | en | en_US |
dc.publisher | EDP Sciences | en_US |
dc.rights | © EDP Sciences, SMAI 2021 | en_US |
dc.rights | The original publication is available at https://www.esaim-cocv.org/. | en_US |
dc.rights | The following publication Xie, T., Wang, B. C., & Huang, J. (2021). Robust linear quadratic mean field social control: A direct approach. ESAIM: Control, Optimisation and Calculus of Variations, 27, 20 is available at https://doi.org/10.1051/cocv/2021021 | en_US |
dc.subject | Forward-backward stochastic differential equation | en_US |
dc.subject | Linear quadratic control | en_US |
dc.subject | Mean field game | en_US |
dc.subject | Model uncertainty | en_US |
dc.subject | Social optimality | en_US |
dc.title | Robust linear quadratic mean field social control : a direct approach | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.volume | 27 | en_US |
dc.identifier.doi | 10.1051/cocv/2021021 | en_US |
dcterms.abstract | This paper investigates a robust linear quadratic mean field team control problem. The model involves a global uncertainty drift which is common for a large number of weakly-coupled interactive agents. All agents treat the uncertainty as an adversarial agent to obtain a "worst case"disturbance. The direct approach is applied to solve the robust social control problem, where the state weight is allowed to be indefinite. Using variational analysis, we first obtain a set of forward-backward stochastic differential equations (FBSDEs) and the centralized controls which contain the population state average. Then the decentralized feedback-type controls are designed by mean field heuristics. Finally, the relevant asymptotically social optimality is further proved under proper conditions. | en_US |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | ESAIM. Control, optimisation and calculus of variations, 2021, v. 27, 20 | en_US |
dcterms.isPartOf | ESAIM. Control, optimisation and calculus of variations | en_US |
dcterms.issued | 2021 | - |
dc.identifier.scopus | 2-s2.0-85103518422 | - |
dc.identifier.eissn | 1262-3377 | en_US |
dc.identifier.artn | 20 | en_US |
dc.description.validate | 202208 bcfc | en_US |
dc.description.oa | Version of Record | en_US |
dc.identifier.FolderNumber | AMA-0073 | - |
dc.description.fundingSource | RGC | en_US |
dc.description.pubStatus | Published | en_US |
dc.identifier.OPUS | 54171076 | - |
Appears in Collections: | Journal/Magazine Article |
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File | Description | Size | Format | |
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cocv200269.pdf | 511.52 kB | Adobe PDF | View/Open |
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