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Maximum Principle for Stochastic Control System with Elephant Memory and Jump Diffusion

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Abstract

Motivated by a duopoly game problem, the authors study an optimal control problem where the system is driven by Brownian motion and Poisson point process and has elephant memory for the control variable and the state variable. Firstly, the authors establish the unique solvability of an anticipated backward stochastic differential equation, derive a stochastic maximum principle, and prove a verification theorem for the aforementioned optimal control problem. Furthermore, the authors generalize these results to nonzero-sum stochastic differential game problems. Finally, the authors apply the theoretical results to the duopoly game problem and obtain the corresponding Nash equilibrium solution.

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Correspondence to Guangchen Wang.

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The authors declare no conflict of interest.

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This research was supported by the National Key R&D Program of China under Grant No. 2022YFA1006103, the National Natural Science Foundation of China under Grant Nos. 61821004, 61925306, 11831010, 71973084, and 61977043, and the National Science Foundation of Shandong Province under Grant Nos. ZR2019ZD42 and ZR2020ZD24.

This paper was recommended for publication by Editor LI Xun.

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Feng, S., Gao, L., Wang, G. et al. Maximum Principle for Stochastic Control System with Elephant Memory and Jump Diffusion. J Syst Sci Complex 37, 1392–1412 (2024). https://doi.org/10.1007/s11424-024-3163-7

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  • DOI: https://doi.org/10.1007/s11424-024-3163-7

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