IDEAS home Printed from https://ideas.repec.org/h/ito/pchaps/147447.html
   My bibliography  Save this book chapter

Stochastic Leader-Follower Differential Game with Asymmetric Information

In: Game Theory - Applications in Logistics and Economy

Author

Listed:
  • Jingtao Shi

Abstract

In this chapter, we discuss a leader-follower (also called Stackelberg) stochastic differential game with asymmetric information. Here the word "asymmetric" means that the available information of the follower is some sub- ? -algebra of that available to the leader, though they play as different roles in the classical literatures. Stackelberg equilibrium is represented by the stochastic versions of Pontryagin's maximum principle and verification theorem with partial information. A linear-quadratic (LQ) leader-follower stochastic differential game with asymmetric information is studied as applications. If some system of Riccati equations is solvable, the Stackelberg equilibrium admits a state feedback representation.

Suggested Citation

  • Jingtao Shi, 2018. "Stochastic Leader-Follower Differential Game with Asymmetric Information," Chapters, in: Danijela Tuljak-Suban (ed.), Game Theory - Applications in Logistics and Economy, IntechOpen.
    • Handle: RePEc:ito:pchaps:147447
    DOI: 10.5772/intechopen.75413
    as

    Download full text from publisher

    File URL: https://www.intechopen.com/chapters/60490
    Download Restriction: no
    File URL: https://libkey.io/10.5772/intechopen.75413?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zahrate El Oula Frihi & Julian Barreiro-Gomez & Salah Eddine Choutri & Hamidou Tembine, 2020. "Hierarchical Structures and Leadership Design in Mean-Field-Type Games with Polynomial Cost," Games, MDPI, vol. 11(3), pages 1-26, August.
    2. Yan Wang & Lei Wang & Kok Lay Teo, 2018. "Necessary and Sufficient Optimality Conditions for Regular–Singular Stochastic Differential Games with Asymmetric Information," Journal of Optimization Theory and Applications, Springer, vol. 179(2), pages 501-532, November.
    3. Zheng, Yueyang & Shi, Jingtao, 2022. "A linear-quadratic partially observed Stackelberg stochastic differential game with application," Applied Mathematics and Computation, Elsevier, vol. 420(C).
    4. Yueyang Zheng & Jingtao Shi, 2020. "A Stackelberg Game of Backward Stochastic Differential Equations with Applications," Dynamic Games and Applications, Springer, vol. 10(4), pages 968-992, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ito:pchaps:147447. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Slobodan Momcilovic (email available below). General contact details of provider: http://www.intechopen.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.