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  "documentTitle": "2021 Air Street Capital The State of AI Report 2021",
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      "text": "MuZero is the latest member of DeepMind’s “Zero” family. It matches AlphaZero’s performance on Go, chess and Shogi, and outperforms all existing models on the Atari benchmark while learning solely within a world model.",
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      "text": "DeepMind's previous successful algorithms relied on being given the precise game dynamics, which they used for planning. For very complex and unstructured games, this approach doesn't scale well.\nMuZero learns exclusively within a world model, meaning it learns a model of the game's dynamics.\nBut learning a complete model of these dynamics is a hard task. MuZero instead only models what is relevant to its decision making, enabling it to scale well to complex games.\nThe Atari benchmark is a suite of visually complex games which had been beyond the reach of model-based systems. MuZero now outperforms the best model-free systems on Atari, while performing as well as state of the art algorithms on Go, chess, and Shogi.",
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      "text": "MuZero is the latest member of DeepMind's “Zero” family. It matches AlphaZero's performance on Go, chess and Shogi, and outperforms all existing models on the Atari benchmark while learning solely within a world model. Muzero appeared in Nature in December 2020.",
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      "text": "Games continue to drive Reinforcement Learning research",
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