从GDELT数据库挖掘国际政治规范
Mining International Political Norms from the GDELT Database
摘要：
长期以来，研究人员一直对规范在多智能体系统中管理智能体行为中的作用感兴趣。在将人类社会的规范性概念正式化并使其适应开放软件系统的管理方面，以及在人类和人工社会中的规范性过程的模拟方面，已经做了很多工作。然而，一直有相对较少的工作应用规范MAS机制，以了解人类社会的规范。本书将在国际政治的背景下探讨这一问题。使用GDELT数据集，包含从新闻报道中提取的国际事件的机器编码记录，我们提取了国家间事件的双边序列，并应用贝叶斯规范挖掘机制来识别最能解释观察到的行为的规范。统计评价表明，规范模型拟合数据明显优于概率离散事件模型。
英文摘要：
Researchers have long been interested in the role that norms can play in governing agent actions in multi-agent systems. Much work has been done on formalising normative concepts from human society and adapting them for the government of open software systems, and on the simulation of normative processes in human and artificial societies. However, there has been comparatively little work on applying normative MAS mechanisms to understanding the norms in human society. This work investigates this issue in the context of international politics. Using the GDELT dataset, containing machine-encoded records of international events extracted from news reports, we extracted bilateral sequences of inter-country events and applied a Bayesian norm mining mechanism to identify norms that best explained the observed behaviour. A statistical evaluation showed that the normative model fitted the data significantly better than a probabilistic discrete event model.
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