High-Fidelity Computational Social Science in Anthropology: Prospects for Developing a Comparative Framework

Approaches to modeling social phenomena vary on a continuum from simple models, in which causality is clear and parameters few, to realistic, high-fidelity models designed to capture the most detailed system behavior possible in a specific setting. Anthropologists have produced both simple and high-fidelity models. The focus of this article is on high-fidelity modeling in anthropology and the special challenge its complexity presents for model comparison. Useful model comparison requires docking, or rendering models comparable, and the author presents a framework for docking based on the work of Axelrod, and Cioffi-Revilla and Gotts. Docking not only renders models more comparable, allowing for more traditional theory testing, but it also sharpens the discussion about the ontology of anthropological phenomena and how they are best represented as theories and models