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Optimal Reinforcement Learning-Based Control Algorithm for a Class of Nonlinear Macroeconomic Systems

Author

Listed:
  • Qing Ding

    (College of Liberal Arts and Sciences, National University of Defense Technology, Changsha 410073, China
    College of Mathematics and Statistics, Hunan University of Finance and Economics, Changsha 410205, China)

  • Hadi Jahanshahi

    (Department of Mechanical Engineering, University of Manitoba, Winnipeg, MB R3T 5V6, Canada)

  • Ye Wang

    (Department of Mathematics, Huzhou University, Huzhou 313000, China
    Institute for Advanced Study Honoring Chen Jian Gong, Hangzhou Normal University, Hangzhou 311121, China)

  • Stelios Bekiros

    (Department of Banking and Finance, FEMA, University of Malta, MSD 2080 Msida, Malta
    Department of Economics, European University Institute, I-50014 Florence, Italy)

  • Madini O. Alassafi

    (Department of Information Technology, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 21589, Saudi Arabia)

Abstract

Due to the vital role of financial systems in today’s sophisticated world, applying intelligent controllers through management strategies is of crucial importance. We propose to formulate the control problem of the macroeconomic system as an optimization problem and find optimal actions using a reinforcement learning algorithm. Using the Q-learning algorithm, the best optimal action for the system is obtained, and the behavior of the system is controlled. We illustrate that it is possible to control the nonlinear dynamics of the macroeconomic systems using restricted actuation. The highly effective performance of the proposed controller for uncertain systems is demonstrated. The simulation results evidently confirm that the proposed controller satisfies the expected performance. In addition, the numerical simulations clearly confirm that even when we confined the control actions, the proposed controller effectively finds optimal actions for the nonlinear macroeconomic system.

Suggested Citation

  • Qing Ding & Hadi Jahanshahi & Ye Wang & Stelios Bekiros & Madini O. Alassafi, 2022. "Optimal Reinforcement Learning-Based Control Algorithm for a Class of Nonlinear Macroeconomic Systems," Mathematics, MDPI, vol. 10(3), pages 1-13, February.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:3:p:499-:d:741823
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    References listed on IDEAS

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    1. Jahanshahi, Hadi & Yousefpour, Amin & Munoz-Pacheco, Jesus M. & Kacar, Sezgin & Pham, Viet-Thanh & Alsaadi, Fawaz E., 2020. "A new fractional-order hyperchaotic memristor oscillator: Dynamic analysis, robust adaptive synchronization, and its application to voice encryption," Applied Mathematics and Computation, Elsevier, vol. 383(C).
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    Cited by:

    1. Qijia Yao & Hadi Jahanshahi & Larissa M. Batrancea & Naif D. Alotaibi & Mircea-Iosif Rus, 2022. "Fixed-Time Output-Constrained Synchronization of Unknown Chaotic Financial Systems Using Neural Learning," Mathematics, MDPI, vol. 10(19), pages 1-14, October.

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