Using stakeholders’ narratives to build an agent-based simulation of a political process

Abstract

When reviewing the present state of the art in agent-based models of social processes, one may encounter three basic types of models: theory-based models start with a set of assumptions about human behavior and test those assumptions in various scenarios; data-driven models are based on mass data (e.g. census, large surveys) and usually include a large number of agents; a third group of models combines different data sources and may also include qualitative information, that is, text descriptions of human behavior. Pushing this notion further, the motivation of this paper is to demonstrate how an agent-based model of a political process can be designed only using the stakeholders’ own descriptions and observation results. The simulation reproduces the discussions among the stakeholders and their subsequent decisions and is able to react to changes in their general settings. The simulation outcomes are also produced in text format so that they are easily understandable to stakeholders and other users. The simulation can be used to explore different sets of rules for the decision processes and their results.

Applications of ABM in International Legal Research: The Case of Compliance

“…A number of problems arise from this set-up, chiefly perhaps the definition of what constitutes a successful intervention -it is difficult to assess the contribution that an NGO has made to the compliance process, and correspondingly difficult to translate it into traceable model outcomes. Secondly, the translation of qualitative research (interviews, text analysis) and legal norms into mechanisms within the model presents a challenge, which is well-documented and has been tackled for other fields of application [13,14,15].…”