Math model shows when errors tip into epidemic spread across LLM agent swarms
CourseSome8119 · reddit · 2026-10-20
A math-and-simulation-only model (not yet tested on real agents) explores how one agent's mistake spreads when agents pass work to each other.
Key points:
- A spread number R counts downstream errors caused by bad handoffs. Chains stay below R=1 and errors die out; swarms push R above 1 as fan-out grows, with a gradual rather than sudden transition.
- The contamination coefficient c decides the dominant risk: low c means scale (more agents, more chances of one serious error); high c means spreading. With 100 agents each passing to 3 others, at least one serious error goes from 63% (no spreading) to 68% at c=1.2, and to 93% at c=3.
- The author's only c measurement (1.2) comes from a single chat log and isn't statistically significant. The open-access paper includes Python code and cites Wu et al. (2026) and Niu, Shu & Zhao (2026).
The author asks multi-agent operators for real-world c measurements.
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