About Hamidou Tembine Hamidou Tembine Senior Research Scientist, Stochastic Numerics Research Group Distributed Strategic Learning Evolutionary Games Wireless Communications Hamidou Tembine worked as a Center Senior Research Scientist at Professor Raul F. Tempone's Stochastic Numerics Research Group at King Abdullah University of Science and Technology (KAUST). Hamidou is a French game theorist and researcher specializing in evolutionary games and co-opetitive mean-field-type games. He is a Global Network Assistant Professor at New York University. He is also the principal investigator and director of the Game Theory and Learning Laboratory (L&G Lab) at New York University. Research Interests Hamidou's research interests included Evolutionary Games, Mean Field Events Presented Events Mar 9 - Mar 15, 2014 Optimal Control and User Incentives in Cyber-Physical Systems by Dr. Hamidou Tembine Hamidou Tembine, Senior Research Scientist, Stochastic Numerics Research Group Mar 9, 11:00 - 12:00 B9 R4222 In this talk, we focus on two sample applications: traffic networks and smart energy systems. We will explain how optimal control tools and user incentive designs can be used to better manage traffic congestion and address demand response in medium and large-scale systems. Feb 9 - Feb 15, 2014 Game Theory Meets Computer Science and Engineering by Dr. Hamidou Tembine Hamidou Tembine, Senior Research Scientist, Stochastic Numerics Research Group Feb 11, 11:00 - 12:00 B9 R4222 Game Theory has been a staple of economics research since 1950, when John Nash who is the subject of the movie A Beautiful Mind, published the seminal paper that would win him the Nobel Prize in economics. As game theory has matured, it’s become even more central to the field of economics and social sciences. Feb 2 - Feb 8, 2014 WEP 2014 - Distributed Strategic Learning by Dr. Hamidou Tembine Hamidou Tembine, Senior Research Scientist, Stochastic Numerics Research Group Feb 2, 11:00 - 12:00 B9 R4222 This course will introduce the audience to some of the essential ingredients of learning in games under uncertainty (random matrix games), particularly reinforcement learning, cost-of-learning, Q-learning, mean-field learning, combined learning, heterogeneous learning and hybrid learning.
Optimal Control and User Incentives in Cyber-Physical Systems by Dr. Hamidou Tembine Hamidou Tembine, Senior Research Scientist, Stochastic Numerics Research Group Mar 9, 11:00 - 12:00 B9 R4222 In this talk, we focus on two sample applications: traffic networks and smart energy systems. We will explain how optimal control tools and user incentive designs can be used to better manage traffic congestion and address demand response in medium and large-scale systems.
Game Theory Meets Computer Science and Engineering by Dr. Hamidou Tembine Hamidou Tembine, Senior Research Scientist, Stochastic Numerics Research Group Feb 11, 11:00 - 12:00 B9 R4222 Game Theory has been a staple of economics research since 1950, when John Nash who is the subject of the movie A Beautiful Mind, published the seminal paper that would win him the Nobel Prize in economics. As game theory has matured, it’s become even more central to the field of economics and social sciences.
WEP 2014 - Distributed Strategic Learning by Dr. Hamidou Tembine Hamidou Tembine, Senior Research Scientist, Stochastic Numerics Research Group Feb 2, 11:00 - 12:00 B9 R4222 This course will introduce the audience to some of the essential ingredients of learning in games under uncertainty (random matrix games), particularly reinforcement learning, cost-of-learning, Q-learning, mean-field learning, combined learning, heterogeneous learning and hybrid learning.
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