A reinforcement-learning algorithm that combines a tree-based search with a learned model achieves superhuman performance in high-performance planning and visually complex domains, without any knowledge of their underlying dynamics.
MuZero, which was first introduced in a preliminary paper in 2019, masters Go, chess, shogi and Atari without needing to be told the rules, thanks to its ability to plan winning strategies in unknown environments. Read more: https://t.co/15nrE0jRv1
— DeepMind (@DeepMind) December 23, 2020
SOURCE: Nature