The unknotting number, hard unknot diagrams, and reinforcement learning
<|reference_start|>The unknotting number, hard unknot diagrams, and reinforcement learning: 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.<|reference_end|>
@article{applebaum2024the,
    title={The unknotting number, hard unknot diagrams, and reinforcement learning},
    author={Taylor Applebaum, Sam Blackwell, Alex Davies, Thomas Edlich, Andr'as
  Juh'asz, Marc Lackenby, Nenad Tomav{s}ev, Daniel Zheng},
    journal={arXiv preprint arXiv:2409.09032},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.09032},
    primaryClass={math.GT cs.AI cs.LG}
}