and

One of the key challenges in designing expert systems is a credible represen-tation of uncertainty and partial belief. During the past deca.de, a number of rule-based belief languages were proposed and implemented in applied sys-tems. Due to their quasi-probabilistic nature, the external validity of these languages is an open question. This paper discusses the theory of belief re-vision in expert systems through a canonical belief calculus model which is invariant across different languages. A zeta-interpreter for non-categorical reasoning is then presented. The purposes of this logic model is twofold: first, it provides a clear and concise conceptualization of belief representa-tion and propagation in rule-based systems. Second, it serves as a working shell which can be instantiated with different belief calculi. This enables experiments to investigate the net impact of alternative belief languages on the exbernal validity of a fixed expert system