Empirical investigation of knowledge representation servers: design issues and applications experience with KRS

ABSTRACT

The design and application of KRS, a knowledge representation server in the KL-ONE, KRYPTON, CLASSIC family, are described. The server is designed as an open architecture module that can be used as a stand-alone service or embedded in other systems. It accepts the constraints necessary to make subsumption and recognition tractable, and maintains a careful distinction between definitions and assertions. It is implemented as a class library in an object-oriented language using generic, reusable objects. The approach taken to the integration of the server with external knowledge representation servers of similar or dissimilar types is analyzed. The server supports reasoning with exceptions and incomplete data through computation of a three-valued subsumption relation that is able to determine the possibility of further inferences if more assertions are made. KRS demonstrates that it is now possible to develop knowledge representation servers on a par with floating-point arithmetic units and numeric libraries, as modules with well-defined functionality and fast, reliable performance. It is also proving a useful tool for the empirical investigation of some large-scale knowledge representation server applications.

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INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE

Additional Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE

General Terms:
Design, Measurement, Performance, Theory