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Discrete–Time Stochastic Control and Dynamic Potential Games [electronic resource] : The Euler–Equation Approach / by David González-Sánchez, Onésimo Hernández-Lerma.

By: González-Sánchez, David [author.].
Contributor(s): Hernández-Lerma, Onésimo [author.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: SpringerBriefs in Mathematics: Publisher: Cham : Springer International Publishing : Imprint: Springer, 2013Description: XIV, 69 p. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319010595.Subject(s): Mathematics | Systems theory | Distribution (Probability theory) | Mathematics | Systems Theory, Control | Probability Theory and Stochastic Processes | ControlDDC classification: 519 Online resources: Click here to access online
Contents:
Introduction and summary.- Direct problem: the Euler equation approach.- The inverse optimal control problem.- Dynamic games -- Conclusion -- References -- Index.
In: Springer eBooksSummary: There are several techniques to study noncooperative dynamic games, such as dynamic programming and the maximum principle (also called the Lagrange method). It turns out, however, that one way to characterize dynamic potential games requires to analyze inverse optimal control problems, and it is here where the Euler equation approach comes in because it is particularly well–suited to solve inverse problems. Despite the importance of dynamic potential games, there is no systematic study about them. This monograph is the first attempt to provide a systematic, self–contained presentation of stochastic dynamic potential games.
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Introduction and summary.- Direct problem: the Euler equation approach.- The inverse optimal control problem.- Dynamic games -- Conclusion -- References -- Index.

There are several techniques to study noncooperative dynamic games, such as dynamic programming and the maximum principle (also called the Lagrange method). It turns out, however, that one way to characterize dynamic potential games requires to analyze inverse optimal control problems, and it is here where the Euler equation approach comes in because it is particularly well–suited to solve inverse problems. Despite the importance of dynamic potential games, there is no systematic study about them. This monograph is the first attempt to provide a systematic, self–contained presentation of stochastic dynamic potential games.

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