Knowledge Engineering under Time and Uncertainty

From Distributed Information and Intelligence Analysis Group

A Bayesian Knowledge Fragment based on a news article from the 2008 South Carolina Democratic Primary

We work continually on developing new knowledge engineering models, frameworks, and tools. We are especially interested in reasoning under uncertainty. This can be uncertainty about the truth of a proposition or when an event may occur. The primary framework we employ is that of Bayesian Knowledge Bases (BKBs). A modeling framework that subsumes Bayesian Networks, BKBs have been extended to support temporal knowledge, and extensive work has been done on verification and validation techniques for them.