# Tsinghua team's Algebraic World Model lets AI reason about rules from experiments

> Original title: 清华姚期智团队新作：代数世界模型，让AI像牛顿一样思考

- Source: QbitAI
- Published: 2026-11-01T08:02:37.000Z
- Bad Influence: https://badinfluence.news/items/bl6ccu00uldfi88t9v95eh8hg
- Original: https://www.qbitai.com/2026/11/507031.html

## Summary

Tsinghua University researchers led by Yao Qizhi and Yuan Yang present the Algebraic World Model (AWM), which turns AI game exploration into executable Python hypotheses, refines them, and formalizes them in Lean 4. On the ARC-AGI-3 test set, AWM reports clearing all 183 levels with Opus 5 at a 99.9% score, using 43% of the human baseline's average actions. The article says the model also proved that one altered level was unsolvable at its step limit, where GPT-6 Astra and Claude Opus 5.5 gave wrong answers.