mlsanityData to 14 Oct 2026

An application of neural networks to a problem in knot theory and group theory (untangling braids)

arXiv 2206.05373 ↗First posted 10 Jun 2022math.GT cs.LGcited by 2

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Abstract (arXiv)

We report on our success on solving the problem of untangling braids up to length 20 and width 4. We use feed-forward neural networks in the framework of reinforcement learning to train the agent to choose Reidemeister moves to untangle braids in the minimal number of moves.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 2 of its 7 references that are in the map. First posted on arXiv 10 Jun 2022.

Builds on

2 of 7 references.

References · 2

  1. 2020Learning to Unknotcited by 40
  2. 2021Untangling Braids with Multi-agent Q-Learningcited by 3

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 1; 2024: 0; 2025: 0; 2026: 1.

2 papers.

  1. 2023Geometric deep learning approach to knot theorycited by 1
  2. 2026Learning the Word Problem: Geodesic Lengths and Cryptographic Applicationscited by 0