mlsanityData to 7 Oct 2026

The unknotting number, hard unknot diagrams, and reinforcement learning

arXiv 2409.09032 ↗First posted 13 Sep 2024math.GT cs.AI cs.LGcited by 2

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Abstract (arXiv)

We have developed a reinforcement learning agent that often finds a minimal sequence of unknotting crossing changes for a knot diagram with up to 200 crossings, hence giving an upper bound on the unknotting number. We have used this to determine the unknotting number of 57k knots. We took diagrams of connected sums of such knots with oppositely signed signatures, where the summands were overlaid. The agent has found examples where several of the crossing changes in an unknotting collection of crossings result in hyperbolic knots. Based on this, we have shown that, given knots K and K' that satisfy some mild assumptions, there is a diagram of their connected sum and u(K) + u(K') unknotting crossings such that changing any one of them results in a prime knot. As a by-product, we have obtained a dataset of 2.6 million distinct hard unknot diagrams; most of them under 35 crossings. Assuming the additivity of the unknotting number, we have determined the unknotting number of 43 at most 12-crossing knots for which the unknotting number is unknown.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 5 of its 35 references that are in the map. First posted on arXiv 13 Sep 2024.

Builds on

5 of 35 references.

References · 5

  1. 2017Attention Is All You Needcited by 59,932
  2. 2016Generative Adversarial Imitation Learningcited by 1,576
  3. 2018IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architecturescited by 866
  4. 2021IQ-Learn: Inverse soft-Q Learning for Imitationcited by 191
  5. 2020Learning to Unknotcited by 40

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Cited by year (2026 to 7 Oct)

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

2 papers.