Physical Society Colloquium
Deep Reinforcement Learning: From Basics to Applications
School of Computer Science McGill University
In recent years, significant progress has been made in solving challenging
problems across various domains using deep reinforcement learning. In this
talk I will review basic models and algorithms for this paradigm and will
describe several applications, ranging from healthcare to robotics. I will
also discuss challenges that arise in experimental techniques and reporting
procedures in deep RL.
Friday, September 7th 2018, 15:30
Ernest Rutherford Physics Building, Keys Auditorium (room 112)
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