A Lightweight Social Computing Approach to Emergency Management Policy Selection
提出一种轻量级社会计算方法，通过僵尸城市模型模拟人工社会，支持应急管理政策的迭代选择、评估与调整，并以传染病传播案例验证其有效性。
In order to select effective policies for emergency management in a timely manner, this paper proposes an agile and lightweight social computing approach to facilitating policy selection, evaluation, and adjustment relative to emergency management in both quantitative and qualitative ways. The approach consists of three components represented as PZE: 1) (P) emergency management policy selecting; 2) (Z) modeling artificial societies with the zombie-city model (a general and formal artificial society model); and 3) (E) policy evaluation. The formal specification of the zombie-city model and rigorous expressions of scenarios enable rigorous description and formal reasoning of an artificial society. A feedback loop of this approach supports the iterative adjustment of emergency management policies and the creation of more effective policies. This approach is verified by applying it to a case of an infectious disease transmission with quantitative evaluations, qualitative reasoning and analysis, and iterative adjustments. Results indicate effective emergency management policies can be established with the approach in an iterative way. In contrast with existing research, our proposed approach offers the benefits of being simple, general, rapidly adaptive to changes, and low cost.