Convince: A Conversational Inference Consolidation Engine

Abstract
An operational domain-independent decision-aiding system for situation assessment tasks is described. The system elicits the user's perception of a given situation through a stylized English dialogue and focuses the user's attention on the issue of highest relevancy. Elicited problems are structured as networks where nodes represent variables and directed links represent causal relationships. The system uses a Bayesian inference procedure which combines causal and diagnostic reasoning using a bidirectional propagation of evidence in the form of belief parameters. Upon completion of the dialogue the system provides a formal structure representing relevant propositions, their interrelations, and their updated belief distributions.

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