RUM (Reasoning with Uncertainty Module) and RUMrunner (RUM’s Run Time System)

Abstract

RUM (Reasoning with Uncertainty Module) is an integrated software tool based on KEE, a frame system implemented in an object oriented language. RUM’s architecture is composed of three layers: representation, inference, and control. The representation layer is based on frame-like data structures that capture the uncertainty information used in the inference layer and the uncertainty meta-information used in the control layer. The inference layer provides a selection of five T-norm based uncertainty calculi with which to perform the intersection, detachment, union, and pooling of information. The control layer uses the meta-information to select the appropriate calculus for each context and to resolve eventual ignorance or conflict in the information. This layer also provides a context mechanism that allows the system to focus on the relevant portion of the knowledge base, and an uncertain-belief revision system that incrementally updates the certainty values of well-formed formulae (wffs) in an acyclic directed deduction graph.

RUMrunner, RUM’s real-time counterpart, has two major components: a knowledge base compiler and a run-time inference engine. The KB compiler is used to avoid unnecessary run-time checks, searches, and value substitutions. The output of the KB compiler is a RETE-like network, which is interpreted by the run-time inference engine. This engine is capable of asynchronous processing, task scheduling, interrupt handling, rule class scoped forward/backward chaining, and planning to meet time-deadlines.