Agent-based simulation for border crossing modeling

Abstract

The aim of this study is to build a computational model to simulate border crossing. Since the 19th century, many theories have been applied to the study of international migration phenomena. These theories cover sociological, economical, and cultural aspects. All the theories aim at estimating the magnitude of population movements. Multi-Agent Systems (MAS) are presented as a new methodological approach to model and foresee the process of migration. This article discusses how legal aspects can also be treated from a computational point of view. When a migrant reaches the border checkpoint, he/she must deal with the legislation of the destination country, which is applied by the border security police. This interaction at the microlevel between the migrant and the border agent is based on the definition of a behavioral model that includes the migrant's profile, the border officer's profile, and the legislation that rules the border crossing. With this model, the effects at the macrolevel of new policies (which are usually difficult to predict) can be estimated. Changes in legislation or in strictness in applying the existing law at certain borders can influence migration trends; for example, the choice of route. This study presents the main features of the computational model that has been developed to recreate the border-crossing scenario in a Multi-Agent System.