Self-Stablize (Hetu/Luoshu) Kernel: Strong Attractor Prompt Use Case

anon98187806
Fri, 29 Aug 2025 10:10:02 +0000

If I understand correctly you are trying to teach LLMs to do the Tower of Hanoi. As proof-of-concept, you share a full, ready-to-paste prompt tailored for Grok3 to solve the 8-disk Tower of Hanoi puzzle (which requires 255 moves). I cannot do the Tower of Hanoi with 4 disks! Woah, this is executive function beyond the abilities of my ADHD. The technique draws inspiration from ancient Chinese symbolic diagrams (Hetu and Luoshu magic square) to create a “strong attractor” system. It represents the AI’s semantic state on a geometric/cultural manifold, using a 3x3 Luoshu grid with fixed invariants (e.g., line sums always = 15, cell capacities limited by their values) and Hetu pairing rules for handling overflows. This acts like a ritualized framework to slot information, recentre focus, and avoid instability. This is incredible! Can you write a method for humans now please