Modelling Epistemic Systems

TL;DR

This paper explores modeling approaches, especially agent-based and Bayesian opinion dynamics, to understand how scientific communities form reliable opinions and how different conditions affect the pursuit of trustworthy knowledge.

Contribution

It provides an overview of existing models of scientific communities, emphasizing Bayesian-inspired opinion dynamics to analyze epistemological issues.

Findings

Models can simulate how community conditions influence opinion reliability

Artificial worlds help address epistemological problems in defining truth

Insights into conditions leading to failure in the quest for reliable knowledge

Abstract

In this Chapter, I will explore the use of modeling in order to understand how Science works. I will discuss the modeling of scientific communities, providing a general, non-comprehensive overview of existing models, with a focus on the use of the tools of Agent-Based Modeling and Opinion Dynamics. A special attention will be paid to models inspired by a Bayesian formalism of Opinion Dynamics. The objective of this exploration is to better understand the effect that different conditions might have on the reliability of the opinions of a scientific community. We will see that, by using artificial worlds as exploring grounds, we can prevent some epistemological problems with the definition of truth and obtain insights on the conditions that might cause the quest for more reliable knowledge to fail.