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Modeling Human Reasoning About Information
S. Guarino, J. Pfautz, Z. Cox, and E. Roth
22nd Conference on Uncertainty in Artificial Intelligence, Cambridge, MA (July, 2006)
Information, as well as its qualifiers, or meta-information, forms the basis of human decision-making. Modeling human reasoning therefore requires the development of representations of both information and meta-information. However, while existing models and modeling approaches may include computational technologies that support meta-information 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.
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