Deep reinforcement learning has enabled artificial agents to achieve human-level performance across many challenging domains (for example, playing Atari games and Go). Li Erran Li shares several important algorithms, including deep Q-networks and asynchronous actor-critic algorithms (A3C), discusses major challenges, and explores promising results for making deep reinforcement learning applicable to real-world problems in robotics and natural language processing.
Li Erran Li is a senior research scientist in Uber’s Advanced Technologies Group and an adjunct professor in the Computer Science Department at Columbia University. His current research interests include AI, computer vision, and machine learning algorithms and systems. He is an IEEE fellow and an ACM Fellow. He holds a PhD in computer science from Cornell University, where he was advised by Joseph Halpern.
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