Modeling Human Reasoning About Meta-Information

Abstract

Information, as well as its qualifiers, or meta-information, forms the basis of human deci- sion-making. Human behavior models (HBMs) therefore require the development of repre- sentations of both information and meta-information. However, while existing models and modeling approaches may include computational technologies that support meta-informa- tion analysis, they generally neglect its role in human reasoning. Herein, we describe the application of Bayesian belief networks to model how humans calculate, aggregate, and reason about meta-information when making decisions.