  The purpose of this paper is to report on the most recent developments in our
ongoing investigation of the representation and manipulation of uncertainty in
automated reasoning systems. In our earlier studies (Tong and Shapiro, 1985) we
described a series of experiments with RUBRIC (Tong et al., 1985), a system for
full-text document retrieval, that generated some interesting insights into the
effects of choosing among a class of scalar valued uncertainty calculi. [n
order to extend these results we have begun a new series of experiments with a
larger class of representations and calculi, and to help perform these
experiments we have developed a general purpose inference engine.
