Guarino1, S., Pfautz1, J., Cox1, Z., and Roth2, E.
International Journal of Approximate Reasoning (2009)
Information, as well as its qualifiers, or meta-information, forms the basis of human decision- making. Human behavior models (HBMs) therefore require 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.
For More Information
To learn more or request a copy of a paper (if available), contact S. Guarino.
(Please include your name, address, organization, and the paper reference. Requests without this information will not be honored.)