// ♞ Reinforcement Learning
MuZero
Plans without knowing the rules by learning a value-focused model.
2019 Research frontier extended
IN PLAIN WORDS
Extends AlphaZero with a learned latent dynamics model predicting only reward, value and policy, reaching top performance in Atari and board games.
Used in: Applied to e.g. video-compression rate control
01Original paper
Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model
Julian Schrittwieser, Ioannis Antonoglou, Thomas Hubert, et al. · 2019
arXiv ↗ ✓ Verified · arXiv API
02Where it sits
Learn the left column first; the right column builds on this one.
Learn first
Then you can learn
- Nothing in the atlas builds on it yet
Related:Dreamer (Latent Imagination)World Models
Left: prerequisites · right: builds on this · dashed: related. Full map →
03Learning resources
Official docs, explainers, courses and reference code. All links checked.
Explainers
04Where the course teaches it
For AI / data
- Verification: verified, checked 2026-10-21.
- JSON: /api/learn/algorithms.json (id:
muzero)