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Spatial adaptive crime event simulation with the RA/CA/ABM computational laboratory.

机译:利用RA / CA / ABM计算实验室进行空间适应性犯罪事件模拟。

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An agent-based crime event and crime pattern simulation model is developed in this research. The purpose of the simulation model is to provide a computational laboratory for environmental criminologists to study the interactions among offenders, targets, controllers, and crime places. The simulation model also aims to provide a useful tool for teaching crime event theories.; Routine activity theory and crime pattern theory are the theoretical foundations of the simulation model. Agent-based modeling coupled with cellular automata addresses the complex crime event process of street robbery. A type of spatial autonomous agent is developed with a wayfinding capability on the urban street network. The wayfinding algorithm is based on a reinforcement learning algorithm. Offender agents, target agents and police agents are developed based on the spatial autonomous agent, which can be released on a street network to execute their routine activity schedules. The interactions among offender agents, target agents, police agents, and crime places create crime events and crime patterns for analysis. Offender agents and target agents can learn from their past offending/victimization experience and change their spatial behaviors.; The crime event and crime pattern simulation model is tested to be able to generate credible spatial, temporal, victimization, and offending patterns. The simulation model is then applied to examine the effect of agent adaptations on spatial crime patterns, offending patterns and victimization patterns. The power-function distributions of crime events among crime places and offender population are examined as emphases.; Targeted for MS Windows desktop, the RA/CA/ABM computational laboratory is implemented using Visual C++. The computational laboratory has a graphic user interface that allows users to customize the simulation model, control the simulation process, visualize agent movement and crime patterns during the simulation, and query agent properties and crime patterns during the simulation. The computational laboratory is loosely coupled with Arcview GIS, so that it can take spatial data from Arcview as input, and make use of spatial analytical capabilities of Arcview to analyze the output crime patterns.
机译:本研究建立了基于主体的犯罪事件和犯罪模式模拟模型。模拟模型的目的是为环境犯罪学家提供一个计算实验室,以研究犯罪者,目标,控制者和犯罪地点之间的相互作用。模拟模型还旨在为教授犯罪事件理论提供有用的工具。日常活动理论和犯罪模式理论是模拟模型的理论基础。基于代理的建模与元胞自动机相结合,解决了街头抢劫的复杂犯罪事件过程。在城市街道网络上开发了一种具有寻路能力的空间自治代理。寻路算法基于强化学习算法。罪犯代理人,目标代理人和警察代理人是基于空间自治代理人开发的,可以在街道网络上发布以执行其日常活动时间表。犯罪人,目标人,警察和犯罪场所之间的相互作用会创建犯罪事件和犯罪模式以进行分析。犯罪主体和目标主体可以从过去的犯罪/受害经验中学习,并改变其空间行为。测试犯罪事件和犯罪模式模拟模型以能够生成可靠的空间,时间,受害者和犯罪模式。然后将模拟模型应用于检查特工适应对空间犯罪模式,犯罪模式和受害模式的影响。重点研究犯罪事件在犯罪地点和罪犯人口中的权力函数分布。 RA / CA / ABM计算实验室针对MS Windows桌面,使用Visual C ++实现。计算实验室具有一个图形用户界面,该界面允许用户自定义仿真模型,控制仿真过程,在仿真过程中可视化特工移动和犯罪模式,以及在仿真过程中查询特工属性和犯罪模式。计算实验室与Arcview GIS松散耦合,因此可以将Arcview的空间数据作为输入,并利用Arcview的空间分析功能来分析输出的犯罪模式。

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