Model Based Reinforcement Learning for Atari

ICLR 2020 Łukasz KaiserMohammad BabaeizadehPiotr MiłosBłażej OsińskiRoy H CampbellKonrad CzechowskiDumitru ErhanChelsea FinnPiotr KozakowskiSergey LevineAfroz MohiuddinRyan SepassiGeorge TuckerHenryk Michalewski

Model-free reinforcement learning (RL) can be used to learn effective policies for complex tasks, such as Atari games, even from image observations. However, this typically requires very large amounts of interaction -- substantially more, in fact, than a human would need to learn the same games... (read more)

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