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.
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.
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.
Inhaltsangabe
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.
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.
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