A Methodology for Complex Social Simulations

Claudio Cioffi-Revilla

doi:10.18564/jasss.1528

Abstract

Social simulation — an emerging field of computational social science — has progressed from simple toy models to increasingly realistic models of complex social systems, such as agent-based models where heterogeneous agents interact with changing natural or artificial environments. These larger, multidisciplinary projects require a scientific research methodology distinct from, say, simpler social simulations with more limited scope, intentionally minimal complexity, and typically under a single investigator. This paper proposes a methodology for complex social simulations—particularly inter- and multi-disciplinary socio-natural systems with multi-level architecture—based on a succession of models akin to but distinct from the late Imre Lakatos' notion of a 'research programme'. The proposed methodology is illustrated through examples from the Mason-Smithsonian project on agent-based models of the rise and fall of polities in Inner Asia. While the proposed methodology requires further development, so far it has proven valuable for advancing the scientific objectives of the project and avoiding some pitfalls.

Highlights

1.1 Simple social simulations, such as Conway's life model ( Gardner 1970), Schelling's (1971) segregation model, Heatbugs, or Sugarscape (Epstein and Axtell 1996 ; Bigbee et al 2007), require relatively less methodological planning and developmental stages than more complex social simulations, such as large agent-based models of socio-natural or socio-technical systems
This paper proposes a methodology for complex social simulations— inter- and multi-disciplinary socio-natural systems with multi-level architecture—based on a succession of models akin to but distinct from the late Imre Lakatos' notion of a 'research programme'
In recent years social simulation has progressed from simple toy models such as Conway's or Scheling's to increasingly realistic models of complex social systems, such as agent-based models that include heterogeneous agents interacting in changing natural and/or artificial environments

Summary

Introduction

1.1 Simple social simulations, such as Conway's life model ( Gardner 1970), Schelling's (1971) segregation model, Heatbugs (in Swarm, Netlogo, Repast, or MASON), or Sugarscape (Epstein and Axtell 1996 ; Bigbee et al 2007), require relatively less methodological planning and developmental stages than more complex social simulations, such as large agent-based models of socio-natural or socio-technical systems. 1.3 This article proposes a viable methodology for complex social simulations, for large projects requiring multiple disciplines with the coordinated objective of modeling socio-natural systems with multi-level architecture. This same approach is viable for other complex social simulations, such as computational models of socio-technical systems of coupled social-artificial-natural systems. The methodology is illustrated with the Mason-Smithsonian project on developing agent-based models of the rise and fall of polities in Inner Asia (Cioffi-Revilla et al 2007 ). While this methodology requires further development, at present it has proven valuable for advancing the scientific objectives of the project and for avoiding some pitfalls

A Proposed Methodology for Complex Social Simulation

2.21 Some heuristics for defining a final model M F include

Conclusions