检验生物启发框架是否真比简单设计更可靠。
Do Biological Structural Guarantees Earn Their Complexity?
- 设计三类生物启发机制对比简单模型
- 1000次试验×10个随机种子，超1000万数据点验证
- 首次系统测试生物结构保障的实际收益
受生物系统启发的AI代理框架声称通过基因调控网络、免疫系统和代谢控制中的结构保证带来可靠性提升，但这些主张很少与简单替代方案进行实证对比。本文提出三个深度基准测试：代谢优先门控、基于自诱导剂的群体感应，以及贝叶斯停滞检测，每项均对比生物启发实现、非生物简单版本及消融控制组，在每个种子下运行1000次试验，共10个种子（总计超过1000万数据点）。
原文摘要 · Abstract (English)
Biologically-inspired AI agent frameworks claim reliability benefits through structural guarantees adapted from gene regulatory networks, immune systems, and metabolic control. These claims are rarely tested empirically against simpler alternatives. We present three deep benchmarks: metabolic priority gating, autoinducer-based quorum sensing, and Bayesian stagnation detection, each comparing a biologically-grounded implementation against a naive non-biological alternative and an ablated control, across 1,000 trials per seed and 10 seeds (10M+ data points total).
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