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Mean-Field-Type Games for Engineers

Autor Julian Barreiro-Gomez, Hamidou Tembine
en Limba Engleză Hardback – 18 noi 2021
The contents of this book comprise an appropriate background to start working and doing research on mean-field-type control and game theory. To make the exposition and explanation even easier, we first study the deterministic optimal control and differential linear-quadratic games. Then, we progressively add complexity step-by-step and little-by-little to the problem settings until we finally study and analyze mean-field-type control and game problems incorporating several stochastic processes, e.g., Brownian motions, Poisson jumps, and random coefficients.
We go beyond the Nash equilibrium, which provides a solution for non- cooperative games, by analyzing other game-theoretical concepts such as the Berge, Stackelberg, adversarial/robust, and co-opetitive equilibria. For the mean-field-type game analysis, we provide several numerical examples using a Matlab-based user-friendly toolbox that is available for the free use to the readers of this book.
We present several engineering applications in both continuous and discrete time. Among these applications we find the following: water distribution systems, micro-grid energy storage, stirred tank reactor, mechanism design for evolutionary dynamics, multi-level building evacuation problem, and the COVID-19 propagation control.
"With such a demand from engineering audiences, this book is very timely and provides a thorough study of mean-field-type game theory. The strenuous protagonist of this book is to bridge between the theoretical findings and engineering solutions. The book introduces the basics first, and then mathematical frameworks are elaborately explained. The engineering application examples are shown in detail, and the popular learning approaches are also investigated. Those advantageous characteristics will make this book a comprehensive handbook of many engineering fields for many years, and I will buy one when it gets published."
- Zhu Han
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Specificații

ISBN-13: 9780367566128
ISBN-10: 0367566125
Pagini: 526
Ilustrații: 340
Dimensiuni: 156 x 234 x 29 mm
Greutate: 0.92 kg
Ediția:1
Editura: CRC Press
Colecția CRC Press

Cuprins

I. Preliminaries. 1. Introduction. II. Mean-Field-Free and Mean-Field Games. 2. Mean-Field-Free Games. 3. Mean-Field Games. III. One-Dimensional Mean-Field-Type Games. 4. Continuous-Time Mean-Field-Type Games. 5. Co-opetitive Mean-Field-Type Games. 6. Mean-Field-Type Games with Jump-Di usion and Regime Switching. 7. Mean-Field-Type Stackelberg Games. 8. Berge Equilibrium in Mean-Field-Type Games. IV. Matrix-Valued Mean-Field-Type Games. 9. Matrix-Valued Mean-Field-Type Games. 10. A Class of Constrained Matrix-Valued Mean-Field-Type Games. V. Discrete-Time Mean-Field-Type Games. 11. One-Dimensional Discrete-Time Mean-Field-Type Games. 12. Matrix-Valued Discrete-Time Mean-Field-Type Games. VI. Learning Approaches and Applications. 13. Constrained Mean-Field-Type Games: Stationary Case. 14. Mean-Field-Type Model Predictive Control. 15. Data-Driven Mean-Field-Type Games. 16. Applications.

Notă biografică

Julian Barreiro-Gomez is a Post-Doctoral Associate in the Learning & Game Theory Laboratory (L&G-Lab) at the New York University in Abu Dhabi (NYUAD), United Arab Emirates, and since 2019, he is also with the Research Center on Stability, Instability and Turbulence (SITE) at the New York University in Abu Dhabi (NYUAD).
Hamidou Tembine is presently affiliated with New York University in Abu Dhabi (NYUAD), United Arab Emirates. He is a prolific Researcher and has been co-organizer of several scientific meetings on game theory in networking, wireless Communications, smart energy systems, and smart transportation systems.

Descriere

This book comprises an appropriate background to work and do research on mean-field-type control and game theory. It starts with studying the deterministic optimal control and differential linear-quadratic games, and progressively moves to analyzing mean-field-type control and game problems incorporating several stochastic processes.