Convergence of deep fictitious play for stochastic differential games
Article Properties
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DOI (url)
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Publication Date2022/01/01
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Indian UGC (journal)
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Refrences71
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Citations6
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Jiequn Han Center for Computational Mathematics, Flatiron Institute, 162 5th Avenue, New York, NY, USADepartment of Mathematics, Princeton University, Princeton, NJ, USA
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Ruimeng Hu Department of Mathematics, and Department of Statistics and Applied Probability, University of California, Santa Barbara, CA, USA
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Jihao Long The Program in Applied and Computational Mathematics, Princeton University, Princeton, NJ, USA
Abstract
Cite
Han, Jiequn, et al. “Convergence of Deep Fictitious Play for Stochastic Differential Games”. Frontiers of Mathematical Finance, vol. 1, no. 2, 2022, p. 287, https://doi.org/10.3934/fmf.2021011.
Han, J., Hu, R., & Long, J. (2022). Convergence of deep fictitious play for stochastic differential games. Frontiers of Mathematical Finance, 1(2), 287. https://doi.org/10.3934/fmf.2021011
Han, Jiequn, Ruimeng Hu, and Jihao Long. “Convergence of Deep Fictitious Play for Stochastic Differential Games”. Frontiers of Mathematical Finance 1, no. 2 (2022): 287. https://doi.org/10.3934/fmf.2021011.
Han J, Hu R, Long J. Convergence of deep fictitious play for stochastic differential games. Frontiers of Mathematical Finance. 2022;1(2):287.
Refrences
Citations
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
| Learning High-Dimensional McKean–Vlasov Forward-Backward Stochastic Differential Equations with General Distribution Dependence | SIAM Journal on Numerical Analysis |
| 2024 | |
A computational stochastic dynamic model to assess the risk of breakup in a romantic relationship | Mathematical Methods in the Applied Sciences |
| 2023 | |
| A class of dimension-free metrics for the convergence of empirical measures | Stochastic Processes and their Applications |
| 1 | 2023 |
Dynamics of market making algorithms in dealer markets: Learning and tacit collusion | Mathematical Finance |
| 1 | 2023 |
| Recent Developments in Machine Learning Methods for Stochastic Control and Games | SSRN Electronic Journal | 3 | 2022 |
Citations Analysis
The category
Science: Mathematics 4
is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled Dynamics of Market Making Algorithms in Dealer Markets: Learning and Tacit Collusion and was published in 2022. The most recent citation comes from a 2024 study titled Learning High-Dimensional McKean–Vlasov Forward-Backward Stochastic Differential Equations with General Distribution Dependence. This article reached its peak citation in 2023, with 3 citations. It has been cited in 5 different journals. Among related journals, the SSRN Electronic Journal cited this research the most, with 2 citations. The chart below illustrates the annual citation trends for this article.