sologen.net | Amir-massoud Farahmand – Reinforcement/Machine Learning

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Title	Amir-massoud Farahmand – Reinforcement/Machine Learning
Description	Amir-massoud Farahmand Reinforcement/Machine Learning Researcher Menu Home Research Publications Bio Group Blog Home Faculty Member & Research Scientist C
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Amir-massoud Farahmand Reinforcement/Machine Learning Researcher Menu Home Research Publications Bio Group Blog Home Faculty Member & Research Scientist Canada CIFAR AI Chair at Vector Institute Assistant Professor (status) at the Department of Computer Science , University of Toronto Assistant Professor (cross-appointment) at the Department of Mechanical and Industrial Engineering , University of Toronto Research Overview: My research is in machine learning and particularly in reinforcement learning . My research goal is Designing an agent that controls its stream of experience, by learning how the outside and inside worlds work while focusing on aspects that are most relevant to its decision making. This agent can sample-efficiently solve problems that have (1) large state and action spaces, (2) require decisions to be made at varying temporal granularities, and (3) require risk-awareness. I am interested in understanding the mathematical principles required to design such an agent.

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