基于Agent仿真模型的城市犯罪演化研究——以警力使用优化为例

Research on Urban Crime Evolution Based on Agent Simulation Model——Take the Optimization of the Police Force as an Example

传统上研究人员采用统计方法及组织个体、群体实验来模拟犯罪。但是这些方法由于无法综合模拟个人行为或者由于规模性、经济性等因素而受到限制。基于城市犯罪特点及犯罪学基本理论,采用ABM模型与模拟仿真技术进行城市犯罪的演化研究,希望为警务决策者的警力使用优化提供建议。概述犯罪学经典理论研究及ABM模型相关要素理论,据此得出仿真模型相关参数及规则设置依据,随后基于NetLogo仿真平台开发模拟城市环境并进行城市犯罪仿真实验。结果表明:仿真实验结果对实际警务工作有指导作用,据此在特定时段对警力投入进行调整可以优化警力使用,并充分证明通过模拟仿真的方法可以帮助理解犯罪和改进治理犯罪的过程,并且制定有效的预防犯罪战略。

Traditionally,researchers used statistical methods and organized individual or group experiments to simulate crimes.However,these methods are limited due to the inability to comprehensively simulate individual behaviors or due to factors such as scale and economy.Based on the characteristics of urban crime and the basic theory of criminology,this paper uses ABM model and simulation technology to study the evolution of urban crime,hoping to provide suggestions on the optimization of police use by police decision-makers.This paper summarizes the classic theoretical research of criminology and the related element theory of ABM model.Based on this,the relevant parameters and rule setting basis of the simulation model are obtained.The simulated urban environment is developed based on the NetLogo simulation platform and the urban crime simulation experiment is carried out.The results show that the simulation experiment results can guide the actual police work.According to this,adjusting the police force investment in a specific period can optimize the use of police force,and fully proves that the simulation method can be helpful to understand crime and improve the process of crime management and formulate effective crime prevention strategies.