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Benjamin Van Roy Quote: However, contrary to almost all other anomalocaridids which were active predators, our animal would have been a very peaceful guy.
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Amazon.co.jp: Reinforcement Learning, Bit by Bit (Foundations and Trends(r) in Machine Learning) : Lu, Xiuyuan, Van Roy, Benjamin, Dwaracherla, Vikranth: Foreign Language Books
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Foundations and Trends in Machine Learning Ser.: A Tutorial on Thompson Sampling by Benjamin Van Roy, Zheng Wen, Daniel J. Russo, Abbas Kazerouni and Ian Osband (2018, Trade Paperback) for sale online
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Reinforcement Learning, Bit by Bit (Foundations and Trends(r) in Machine Learning) (Paperback) | Cottage Book Shop
![Benjamin Van Roy - Professor of Electrical Engineering, of Management Science and Engineering, and (by courtesy) of Computer Science Benjamin Van Roy - Professor of Electrical Engineering, of Management Science and Engineering, and (by courtesy) of Computer Science](https://biox.stanford.edu/files/styles/profile_thumbnail/public/benjamin_van_roy_profile.webp?orig=png)
Benjamin Van Roy - Professor of Electrical Engineering, of Management Science and Engineering, and (by courtesy) of Computer Science
![Benjamin Van Roy Quote: However, contrary to almost all other anomalocaridids which were active predators, our animal would have been a very peaceful guy. Benjamin Van Roy Quote: However, contrary to almost all other anomalocaridids which were active predators, our animal would have been a very peaceful guy.](https://minimalistquotes.com/images/however-contrary-to-almost-all-other-anomalocaridi.jpg)
Benjamin Van Roy Quote: However, contrary to almost all other anomalocaridids which were active predators, our animal would have been a very peaceful guy.
![Control Meets Learning Virtual Seminars on X: "Our next talk: March 10: Benjamin Van Roy (Stanford) “Simple Agent, Complex Environment: Efficient Reinforcement Learning with Agent State” Please visit https://t.co/nR5egegFQy for more information ( Control Meets Learning Virtual Seminars on X: "Our next talk: March 10: Benjamin Van Roy (Stanford) “Simple Agent, Complex Environment: Efficient Reinforcement Learning with Agent State” Please visit https://t.co/nR5egegFQy for more information (](https://pbs.twimg.com/media/Ev_P_-rVkAAWTi9.jpg)