Social-Behavioral Modeling for Complex Systems

32 Social‐Behavioral Simulation: Key Challenges

Kathleen M. Carley

Institute of Software Research, School of Computer Science and Engineering and Public Policy, Carnegie Institute of Technology, Carnegie Mellon University, Pittsburgh, PA, 15213, USA

Introduction

Social‐behavioral simulation is often turned to as a way of reasoning about the human condition and thinking through what might happen under various interventions. Potential advantages include overcoming human decision bias, thinking through a large number of alternative situations, and reasoning about context and over periods of time that are too complex for the human unaided by the computation to reason about. While these advantages exist, simulation of complex social‐behavioral systems is not routine. Nor are the simulation models, necessarily, accurate reflections of reality. There are more creditable models where the logics built into the model reflect established theory or empirical regularities. Yet despite best efforts, the logics in these models may reflect human biases. Further, in many simple models and in those where no theory exists, the model may actually reflect simply the potentially nonsensicle opinions of the creators.

Agent‐based (e.g. Bonabeau 2002; Davidsson 2002; van Dam et al. 2012), event history (Box‐Steffensmeier and Jones 2004), Petri net (Tabak and Levis 1985; Murata 1989), and system dynamic models (Sterman 2001; Mohaghegh and Mosleh 2009) are generally used as the simulation ...