Hamid Reza Maei,
an Iranian born physicist, computer scientist and software engineer. He holds a Ph.D. in 2011 from University of Alberta[1], where he was member of the reinforcement learning and artificial intelligence (RLAI) group [2] at the Department of Computing Science[3] to create reinforcement learning algorithms for large-scale problems and was involved in the development of a new family of temporal-difference learning algorithms suitable for value function approximation. The goal of these algorithms was to bring us closer to the development of a universal prediction learning algorithm suitable for learning experientially grounded knowledge of the world [4].
an Iranian born physicist, computer scientist and software engineer. He holds a Ph.D. in 2011 from University of Alberta [1], where he was member of the reinforcement learning and artificial intelligence (RLAI) group [2] at the Department of Computing Science [3] to create reinforcement learning algorithms for large-scale problems and was involved in the development of a new family of temporal-difference learning algorithms suitable for value function approximation. The goal of these algorithms was to bring us closer to the development of a universal prediction learning algorithm suitable for learning experientially grounded knowledge of the world [4].
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