Discrete Time Stochastic Control and Dynamic Potential Games

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 wellsuited 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, selfcontained presentation of stochastic dynamic potential games.

Presents a systematic, comprehensive, self-contained analysis of dynamic potential games, which appears for the first time in book form? Reader-friendly, at a graduate student level Substantial number of examples and applications, mainly from mathematical economics Includes supplementary material: sn.pub/extras

Autorentext
David GonzalezSanchez is Assistant Professor at ITAM Mathematics Department, Mexico City, Mexico. Onesimo HernandezLerma is Professor and Chair, CINVESTAVIPN Mathematics Department, Mexico City, Mexico.

Inhalt
Introduction and summary.- Direct problem: the Euler equation approach.- The inverse optimal control problem.- Dynamic games.- Conclusion.- References.- Index