AI 中文总结
研究在无设计者指定适应度函数时生物发育进化动力学能否产生，通过Genesis平台进行三个实验周期，测试可证伪假设，得出约束驱动选择、智能体介导生态位构建及CPPN间接编码相关结果，还产生了诊断工具和协议。
AI 中文摘要
能否在没有设计者指定适应度函数的情况下产生生物发育的进化动力学？我们展示了Genesis平台，其中智能体栖息在格雷-斯科特反应扩散基质上，仅在物理约束下进化。三个连续的实验周期，每个测试一个可证伪假设，表明：（1）约束驱动选择在完全去除适应度后维持进化活动，但达到硬表型复杂性上限；（2）通过化学分泌的智能体介导的生态位构建是真实的，但因果关系不足以打破该上限；（3）用受NEAT风格物种形成保护的组合模式生成网络（CPPN）间接编码取代固定字母基因组，在无适应度系统中产生了渐进结构复杂化的首个证据。无效结果被视为精确、信息丰富的答案而非失败，产生了可重复使用的诊断工具和适用于任何开放式进化评估管道的假对照协议。
英文摘要
Can evolutionary dynamics characteristic of biological development arise without a designer-specified fitness function? We present Genesis, a platform in which agents inhabit a Gray-Scott reaction-diffusion substrate and evolve under physical constraints alone. Three successive experimental cycles, each testing one falsifiable hypothesis, show: (1) constraint-driven selection sustains evolutionary activity after complete fitness removal but reaches a hard phenotypic complexity ceiling; (2) agent-mediated niche construction via chemical secretion is real but causally insufficient to break that ceiling; and (3) replacing the fixed-alphabet genome with a Compositional Pattern Producing Network (CPPN) indirect encoding, protected by NEAT-style speciation, produces the first evidence of progressive structural complexification in a fitness-free system. Null results are treated as precise, informative answers rather than failures, yielding reusable diagnostic tools and a sham-control protocol applicable to any open-ended evolution evaluation pipeline.
CommentsGECCO Companion '26 Workshop Paper (EvoSelf/ESO Workshop), July 13-17, 2026, San Jose, Costa Rica. 3 pages. ACM ISBN 979-8-4007-2488-6/2026/07
