Dr. Hamidou Tembine
Learning and Game Theory Lab
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20Years (2007-Present)
(Calculated once Scilit publication data is synced: current year − year of first publication + 1)
Representative Publications
View All Publications15 July 2019 in IEEE Access
Journal Article
MJMohammed Jouhari
Mohammed JouhariKIKhalil Ibrahimi
Khalil IbrahimiHamidou TembineJBJalel Ben-Othman
Jalel Ben-Othman
Underwater communication remains a challenging technology via communication cables and the cost of underwater sensor network (UWSN) deployment is still very high. As an alternative, underwater wireless communication has been proposed and have received more attention in the last decade. Preliminary research indicated that the Radio Frequency (RF) and Magneto-Inductive (MI) communication achieve higher data rate in the near field communication. The optical communication achieves good performance when limited to the line-of-sight positioning. The acoustic communication allows long transmission range. However, it suffers from transmission losses and time-varying signal distortion due to its dependency on environmental properties. These latter are salinity, temperature, pressure, depth of transceivers, and the environment geometry. This paper is focused on both the acoustic and magneto-inductive communications, which are the most used technologies for underwater networking. Such as acoustic communication is employed for applications requiring long communication range while the MI is used for real-time communication. Moreover, this paper highlights the trade-off between underwater properties, wireless communication technologies, and communication quality. This can help the researcher community by providing clear insight for further research.
3 May 2012 in IEEE Journal on Selected Areas in Communications
Journal Article
RCRomain Couillet
Romain Couillet
Samir M. PerlazaHamidou TembineMDMerouane Debbah
Merouane Debbah
In this article, we investigate the competitive interaction between electrical vehicles or hybrid oil-electricity vehicles in a Cournot market consisting of electricity transactions to or from an underlying electricity distribution network. We provide a mean field game formulation for this competition, and introduce the set of fundamental differential equations ruling the behavior of the vehicles at the feedback Nash equilibrium, referred here to as the mean field equilibrium. This framework allows for a consistent analysis of the evolution of the price of electricity as well as of the instantaneous electricity demand in the power grid. Simulations precisely quantify those parameters and suggest that significant reduction of the daily electricity peak demand can be achieved by appropriate electricity pricing.
4 December 2009 in IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics)
Journal Article
Hamidou TembineEAEitan Altman
Eitan Altman
RERachid El-Azouzi
Rachid El-Azouzi
YHYezekael Hayel
Yezekael Hayel
We consider a noncooperative interaction among a large population of mobiles that interfere with each other through many local interactions. The first objective of this paper is to extend the evolutionary game framework to allow an arbitrary number of mobiles that are involved in a local interaction. We allow for interactions between mobiles that are not necessarily reciprocal. We study 1) multiple-access control in a slotted Aloha-based wireless network and 2) power control in wideband code-division multiple-access wireless networks. We define and characterize the equilibrium (called evolutionarily stable strategy) for these games and study the influence of wireless channels and pricing on the evolution of dynamics and the equilibrium.
6 November 2013 in IEEE Transactions on Automatic Control
Journal Article
In this paper, we study a class of risk-sensitive mean-field stochastic differential games. We show that under appropriate regularity conditions, the mean-field value of the stochastic differential game with exponentiated integral cost functional coincides with the value function satisfying a Hamilton -Jacobi- Bellman (HJB) equation with an additional quadratic term. We provide an explicit solution of the mean-field best response when the instantaneous cost functions are log-quadratic and the state dynamics are affine in the control. An equivalent mean-field risk-neutral problem is formulated and the corresponding mean-field equilibria are characterized in terms of backward-forward macroscopic McKean-Vlasov equations, Fokker-Planck-Kolmogorov equations, and HJB equations. We provide numerical examples on the mean field behavior to illustrate both linear and McKean-Vlasov dynamics.
29 December 2011 in IEEE Journal on Selected Areas in Communications
Journal Article
MKManzoor Ahmed Khan
Manzoor Ahmed Khan
Hamidou TembineAVAthanasios V. Vasilakos
Athanasios V. Vasilakos
In this paper, we study game dynamics and learning schemes for heterogeneous 4G networks. We introduce a novel learning scheme called cost-to-learn that incorporates the cost to switch, the switching delay, and the cost of changing to a new action and, captures the realistic behavior of the users that we have experimented on OPNET simulations. Considering a dynamic and uncertain environment where the users and operators have only a numerical value of their own payoffs as information, we construct various heterogeneous combined fully distributed payoff and strategy reinforcement learning (CODIPAS-RL): the users try to learn their own optimal payoff and their optimal strategy simultaneously. We establish the asymptotic pseudo-trajectories as solution of differential equations. Using evolutionary game dynamics, we prove the convergence and stability properties in specific classes of dynamic robust games. We provide various numerical examples and OPNET simulations in the context network selection in wireless local area networks (WLAN) and Long Term Evolution (LTE).
1 January 2016 in SIAM Journal on Control and Optimization
Journal Article
Emulation, mimicry, and herding behaviors are phenomena that are observed when multiple social groups interact. To study such phenomena, we consider in this paper a large population of homogeneous ...
About Me
Dr. Hamidou Tembine is the co-founder of Timadie. He graduated in applied mathematics from Ecole Polytechnique (Palaiseau, France) and received a PhD degree from INRIA and University of Avignon, France. He further received his master's degree in game theory and economics. His main research interests are learning, evolution, and games. In 2014, Dr. Tembine received the IEEE ComSoc Outstanding Young Researcher Award for his promising research activities for the benefit of society. He was the recipient of 10+ best paper awards for applications of game theory. Dr. Tembine is a prolific researcher and has authored 300+ scientific publications. He is the author of the book Distributed Strategic Learning for Engineers (published by CRC Press, Taylor & Francis, 2012), which received a book award in 2014, and he is a co-author of the book Game Theory and Learning in Wireless Networks (Elsevier Academic Press) and a co-author of the book Mean-Field-Type Games for Engineers. He has been a visiting researcher at the University of California at Berkeley (US), McGill University (Montreal, Quebec, Canada), the University of Illinois at Urbana-Champaign (UIUC, US), Ecole Polytechnique Federale de Lausanne (EPFL, Switzerland), and the University of Wisconsin (Madison, US). He was a Simons participant and a senior fellow in 2020. He is a senior member of IEEE. He is a next Einstein fellow, class of 2017.