Hamid Reza Maei, M.Sc., M.Phil.
Hamid Reza Maei, M.Sc., M.Phil. is Ph.D. student at the
Reinforcement Learning and Artificial Intelligence laboratory
Computing Science, University of Alberta, Canada.
Hamid builds reinforcement learning algorithms for large-scale problems. Recently he has developed a new family of temporal-difference learning algorithms suitable for value function approximation. The goal of these algorithms is to bring us closer to the development of a universal prediction learning algorithm suitable for learning experientially grounded knowledge of the world.
He coauthored GQ(λ): A general gradient algorithm for temporal-difference prediction learning with eligibility traces, Fast Gradient-Descent Methods for Temporal-Difference Learning with Linear Function Approximation, A Convergent O(n) Algorithm for Off-policy Temporal-difference Learning with Linear Function Approximation, and Convergent Temporal-Difference Learning with Arbitrary Smooth Function Approximation. Read the full list of his publications!
Hamid earned a M.Phil. degree in computational neuroscience at Gatsby Computational Neuroscience Unit, University College London in London, England, earned a Master’s degree in physics from Brandeis University, Boston, USA, and earned a Bachelor’s degree in physics from Sharif University of Technology in Tehran, Iran. He can speak both Persian and English.