Panel: The future of reinforcement learning
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Microsoft Research334 тыс
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02.11.23 – 4721:21
Опубликовано 25 января 2022, 1:29
Speakers:
Geoff Gordon, Partner Researcher, Microsoft Research Montreal
Emma Brunskill, Associate Professor, Computer Science Department, Stanford University
Craig Boutilier, Principal Scientist, Google
Sham Kakade, Senior Principal Researcher, Microsoft Research NYC
Joelle Pineau, Managing Director, Facebook AI Research; Associate Professor, McGill University
Csaba Szepesvari, Team Lead, DeepMind; Professor, University of Alberta
This panel brings together a variety of experts from industry and academia to discuss the question, what is the future of reinforcement learning? Reinforcement learning is an important research area in AI currently, and it has been an important research area in human and animal behavior since at least the middle of the 20th century. More recently, reinforcement learning research has been energized by a series of positive results, often based on deep models, in areas such as personalization and game-playing. However, there remain a wide variety of open questions, both theoretical and practical. We’ll gather expert perspectives on which open questions are the most important as well as where the likely answers might come from.
Learn more about the 2021 Microsoft Research Summit: Aka.ms/researchsummit
Geoff Gordon, Partner Researcher, Microsoft Research Montreal
Emma Brunskill, Associate Professor, Computer Science Department, Stanford University
Craig Boutilier, Principal Scientist, Google
Sham Kakade, Senior Principal Researcher, Microsoft Research NYC
Joelle Pineau, Managing Director, Facebook AI Research; Associate Professor, McGill University
Csaba Szepesvari, Team Lead, DeepMind; Professor, University of Alberta
This panel brings together a variety of experts from industry and academia to discuss the question, what is the future of reinforcement learning? Reinforcement learning is an important research area in AI currently, and it has been an important research area in human and animal behavior since at least the middle of the 20th century. More recently, reinforcement learning research has been energized by a series of positive results, often based on deep models, in areas such as personalization and game-playing. However, there remain a wide variety of open questions, both theoretical and practical. We’ll gather expert perspectives on which open questions are the most important as well as where the likely answers might come from.
Learn more about the 2021 Microsoft Research Summit: Aka.ms/researchsummit
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