What Is the Epistemic Function of Highly Idealized Agent-Based Models of Scientific Inquiry?

Authored by Daniel Frey, Dunja Seselja

Date Published: 2018

DOI: 10.1177/0048393118767085

Sponsors: No sponsors listed

Platforms: NetLogo

Model Documentation: Other Narrative

Model Code URLs: https://github.com/daimpi/SocNetABM/tree/RobIdeal

Abstract

In this paper we examine the epistemic value of highly idealized agent-based models (ABMs) of social aspects of scientific inquiry. On the one hand, we argue that taking the results of such simulations as informative of actual scientific inquiry is unwarranted, at least for the class of models proposed in recent literature. Moreover, we argue that a weaker approach, which takes these models as providing only how-possibly explanations, does not help to improve their epistemic value. On the other hand, we suggest that if ABMs of science underwent two types of robustness analysis, they could indeed have a clear epistemic function, namely by providing evidence for philosophical and historical hypotheses. In this sense, ABMs can obtain evidential and explanatory properties and thus be a useful tool for integrated history and philosophy of science. We illustrate our point with an example of a modelbuilding on the work by Kevin Zollmanwhich we apply to a concrete historical case study.

Tags

Agent-based models Communication networks ROBUSTNESS ANALYSIS Science Eradication Landscapes Communities Cognitive labor Division Worlds Helicobacter-pylori How-possibly explanations Scientific interaction Integrated history and philosophy of science Question