多阶段仿真中指标计算不一致会误导政策优化结果，需用统一接口约束。
Metric Aggregation Divergence: A Hidden Validity Threat in Agent-Based Policy Optimization and a Contractual Remedy
- 在多阶段仿真系统中引入统一的指标计算契约，防止各环节独立处理导致偏差。
- 实验显示64.2%的运行中出现最优策略分歧，83%的模拟中推荐了错误政策。
- 适合关注仿真可靠性、政策优化稳健性的研究人员和开发者。
度量聚合偏差（MAD）是指在基于代理的模型与多目标进化算法结合时，各流水线阶段独立实现从仿真轨迹中提取结果指标，造成隐性不一致。这种不一致源于管道架构层面，各阶段内部自洽，仅在跨阶段输出对比时显现。对已发表的疫情政策工具EpidemiOptim代码分析发现存在三条结构独立的聚合路径。忠实复现该结构后，500次独立运行中64.2%出现冠军策略分歧（95%置信区间[59.9%, 68.3%]）。在300次种子的策略翻转实验中，偏差导致优化器在83%情况下推荐错误冠军，平均福利差距达2.19单位，基尼不平等差距为0.050单位。后续推断审计中，249个种子中有3个越过显著性边界。互补实验在近似可比排名下得到预期零效应（rho=0.991）；公开上游重跑湖问题DPS工作流显示，原发布路径达标率为0.401，而共享契约路径达0.552。本文提出度量契约——在调度时强制各阶段使用单一可调用接口，作为修复方案，其构造上消除偏差，仅增加约3%运行开销。
原文摘要 · Abstract (English)
Metric aggregation divergence (MAD) is the silent inconsistency that arises when distinct pipeline stages in an agent-based model coupled with a multi-objective evolutionary algorithm (ABM+MOEA) independently re-implement how an outcome metric is extracted from simulation trajectories. Unlike deliberate analytical choices, MAD operates at the level of pipeline architecture: each stage is internally coherent, and the inconsistency becomes visible only when cross-stage outputs are compared. Code inspection of EpidemiOptim, a JAIR-published epidemic policy toolbox, reveals three structurally independent aggregation paths in peer-reviewed code. A faithful replication of this structure produces champion disagreement in 64.2% of independent runs (n=500, 95% CI: [59.9%, 68.3%]). In a 300-seed policy-flip experiment, divergent aggregation causes the optimizer to recommend the wrong champion in 83% of replications, with a mean welfare gap of 2.19 units and a Gini inequality gap of 0.050 units. In a follow-up inference audit, 3 of 249 flipped seeds cross the significance boundary itself. A complementary enterprise follow-up produces the predicted null under near-commensurable rankings (rho = 0.991), while a public upstream rerun of the Lake Problem DPS workflow shows that the archived published-path recommendation reaches joint-threshold success 0.401 whereas a shared contract-path rule reaches 0.552. We introduce the metric contract - a single shared callable enforced at dispatch time across all pipeline stages - as the remedy. Framed as standard engineering discipline applied to the cross-stage metric interface, the contract eliminates divergence by construction with approximately 3% runtime overhead.
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