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// ♞ Reinforcement Learning

MuZero

Plans without knowing the rules by learning a value-focused model.

2019 Research frontier extended

Original paper ↓ What to learn first →

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

TIMELINE · prerequisites → this → what builds on it

2016 AlphaGo / Alp…2019 MuZero

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

MuZero

Then you can learn

  • Nothing in the atlas builds on it yet

Related:Dreamer (Latent Imagination)World Models

AlphaGo / Alpha…Dreamer (Latent…World Models MuZero

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

U33 Reinforcement Learning Basics MDPs, Q-learning, DQN, policy gradients, PPO and AlphaZero — the prerequisites for post-training and reasoning models. 14 h12 algorithms4 papers
For AI / data

Data updated: AI algorithms & curriculum(UTC+8)