Parallel Crime Scene Analysis Based on ACP Approach

Abstract

Crime scene analysis is a retrospective process from traces to psychology and physiology. It is not only the starting point and foundation of criminal investigation, but also the key part for solving criminal cases. As a typical open complex social system, it has three features, namely, uncertainty, diversity, and complexity, thus making the system modeling a huge challenge. In this paper, we propose the parallel crime scene analysis system based on the artificial societies, computational experiments and parallel execution (ACP) approach, which uses artificial (A) crime scene to describe the basic elements, functions and states of the criminals, computational (C) experiments to compute and predict the different forms of crime scene, and parallel (P) execution to guide or control the evolution of the physical crime process in accordance with the results from the artificial crime scene. First, we propose the concept of parallel crime scene from the perspective of complex system theory and give an overview of its architecture, then we present the construction method of artificial crime scene and the blackboard-based multiagent artificial crime scene analysis system. On this basis, the temporal and spatial interaction models of the criminal subjects are proposed and verified. After that, we introduce the software-defined crime scene analyzing model systematically. The ACP approach sheds light on the intelligent management and control for complex crime scene analysis.