Treffer: Using a Description Classifier to Enhance Deductive Inference

The representation languages found in many expert system shells are hybrids composed of a frame language and a rule language. Unfortunately, the frame and rule components in these systems are not well integrated, and as a result they miss important classes of inferences. In place of frames, LOOM combines a description language with a rule language, and uses an inference engine called a classifier to achieve a successful integration of framelike knowledge and rule-like knowledge. LOOM's ability to reason with descriptions enables us to implement a broader range of capabilities than those found in the current generation of expert system shells. For example, LOOM is able to detect inconsistencies in a rule base, to match against partially-specified (not fully-grounded) instances, and it implements a generalization of the traditional (e.g., CLOS-like) conception of object-oriented method dispatching. AI Topic: Knowledge Representation, Reasoning Status: KR system in use by more than 15 .