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- Computing and Processing
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Jamal Bentahar
Also published under:J. Bentahar
Affiliation
Department of Computer Science and 6G Research Center, Khalifa University, Abu Dhabi, UAE
Concordia University, Montreal, QC, Canada
Concordia University, Montreal, QC, Canada
Topic
Deep Reinforcement Learning,Internet Of Things,Internet Of Things Devices,Federated Learning,Machine Learning Models,Deep Learning,Reward Function,State Space,Actor Network,Deployment Model,Disc Space,Federated Learning Model,Global Model,Learning Process,Markov Decision Process,Mobile Devices,Proximal Policy Optimization,Anomaly Detection,Base Station,Beginning Of Episode,Breadth-first Search,Central Model,Client Management,Cloud Computing,Complex Environment,Computation Offloading,Decision-making Process,Deep Neural Network,Device Area,Edge Server,Expectation Maximization,Expert Demonstrations,Explainable Artificial Intelligence,Head-mounted Display,Imitation Learning,Internet Of Things Applications,Internet Of Things Systems,Internet Of Vehicles,Learning Environment,Machine Learning,Mobile Edge Computing,Model Selection,Multi-agent Deep Reinforcement Learning,Neural Network,Objective Function,Placement Decisions,Power Calculation,Reinforcement Learning Agent,Service Quality,Target Location,
Biography
Jamal Bentahar received the Ph.D. degree in computer science and software engineering from Laval University, Canada, in 2005. He is a Professor with the Concordia Institute for Information Systems Engineering, Concordia University, Canada. From 2005 to 2006, he was a Postdoctoral Fellow with Laval University and then an NSERC Postdoctoral Fellow with Simon Fraser University, Canada. He was an NSERC Co-Chair for Discovery Grant for Computer Science from 2016 to 2018. He is a Visiting Professor with the Khalifa University of Science and Technology. His research interests include the areas of computational logics, reinforcement learning, multi-agent systems, service computing, game theory, and software engineering.