DeepMind Introduces MuZero That Achieves Superhuman Performance In Tasks Without Learning Their Underlying Dynamics

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Previously, DeepMind has used reinforcement learning to teach programs to master various games such as the Chinese board game ‘Go,’ the Japanese strategy game ‘Shogi,’ chess, and challenging Atari video games, where earlier AI programs were taught the rules first during training.

DeepMind has introduced MuZero, an algorithm that (by combining a tree-based search with a learned model) achieves superhuman performance in several challenging and visually complex domains, without knowing their underlying dynamics. MuZero learns a model that, when applied iteratively, predicts the quantities most directly relevant to planning.

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