信息共享何时改善去中心化发现：聚合、独立救援与均衡选择
原标题：When Does Information Sharing Improve Decentralized Discovery? Aggregation, Independent Rescue, and Equilibrium Selection
AI 摘要
该论文研究信息共享对去中心化发现的影响，指出共享虽能提升共同行动的准确性，但会减少独立救援行动。通过精确的增量共享恒等式，作者得出共享有益的局部条件：当池化残差收缩快于被移除的私有失败因素时。在两人对称博弈中，当信号精度为3/5且相关系数在特定区间时，共享严格改善发现结果，但该结论依赖于均衡选择。
正文节选
[Page 1] When Does Information Sharing Improve Decentralized Discovery? Aggregation, Independent Rescue, and Equilibrium Selection Yohei Nakajima Untapped Capital 2026 July 2026 Sep 1 Information sharing changes both posterior quality and the diversity of actions available for discovery. We study that joint effect in finite one-hit sear