Simulating a Quasi-Simulation: A Framework for Using Multi-Agent Simulation Techniques for Studying MMORPGs

This paper proposes a conceptual framework for using Multi Agent Simulation (MAS) techniques to study Massively Multiplayer Online Role-Playing Games (MMORPGs) as a bridge between social simulation and virtual world research. It argues that social simulation faces three persistent challenges: the difficulty of modeling human subjectivity, the pervasive contingency of real social systems, and the problem of validating simulation outputs against empirical data. The author contends that MMORPGs are partially suited to address these issues, since they involve real human participants rather than purely AI-driven agents, and their sandbox structure limits the range of unmodeled contingencies. The paper's thesis is that MMORPGs function as "quasi-simulations" that can yield research data for understanding the relationship between virtual and real social life.

The conceptual foundation builds on Dimitri Williams' "mapping principle," which describes how virtual worlds correspond to real-world counterparts, and extends it by drawing on Baudrillard's notion of hyperreality. The author adds a "hyperreal" category to Williams' postulates in order to account for the distinct relationship between virtual environments and the social phenomena occurring within them. This refinement is positioned as an alternative framework for interpreting data drawn from MMORPGs.

To illustrate the framework in practice, the paper presents a multi-agent model of social identity (re)production in World of Warcraft, grounded in Javier Salazar's theoretical model of social identity. The computational model reproduces aspects of the game's environment, social processes, and migration patterns, with the aim of demonstrating how meaningful insights into the game's social landscape can be extracted. The paper concludes by offering guidance on applying the framework and identifying unresolved issues linking simulation methodology, MMORPG studies, and virtual world data analysis.