H
Hamidou Tembine
Researcher at New York University Abu Dhabi
Publications - 264
Citations - 4971
Hamidou Tembine is an academic researcher from New York University Abu Dhabi. The author has contributed to research in topics: Game theory & Stochastic game. The author has an hindex of 32, co-authored 263 publications receiving 4258 citations. Previous affiliations of Hamidou Tembine include New York University & French Institute for Research in Computer Science and Automation.
Papers
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Book
Game Theory and Learning for Wireless Networks: Fundamentals and Applications
Samson Lasaulce,Hamidou Tembine +1 more
TL;DR: Game Theory and Learning for Wireless Networks covers how theory can be used to solve prevalent problems in wireless networks such as power control, resource allocation or medium access control and bridges the gap between theory and practice.
Journal ArticleDOI
Evolutionary Games in Wireless Networks
TL;DR: This paper considers a noncooperative interaction among a large population of mobiles that interfere with each other through many local interactions and defines and characterize the equilibrium (called evolutionarily stable strategy) for these games.
Journal ArticleDOI
Underwater Wireless Sensor Networks: A Survey on Enabling Technologies, Localization Protocols, and Internet of Underwater Things
TL;DR: The trade-off between underwater properties, wireless communication technologies, and communication quality is highlighted to help the researcher community by providing clear insight for further research.
Journal ArticleDOI
Electrical Vehicles in the Smart Grid: A Mean Field Game Analysis
TL;DR: A mean field game formulation is provided for this competition, and the set of fundamental differential equations ruling the behavior of the vehicles at the feedback Nash equilibrium is introduced, referred here to as the mean field equilibrium.
MonographDOI
Distributed Strategic Learning for Wireless Engineers
TL;DR: This robust game theory cookbook analyzes games where some parameters are uncertain and random and demonstrates what is needed to learn strategic interaction in wireless networks under uncertainty, randomness, and time delays.