Extensible Knowledge Representation: the Case of Description Reasoners

TL;DR

This paper presents a modular, extensible framework for Description Logics reasoners that supports adding new concept constructors and reasoning capabilities tailored to specific application needs.

Contribution

It introduces a heuristic methodology and software architecture enabling the extension of Description Logics reasoners with new constructors and reasoning strategies.

Findings

Supports both intentional and extensional reasoning

Allows implementation of incomplete reasoners for complex constructors

Facilitates reasoning about application-specific concepts like dates and plans

Abstract

This paper offers an approach to extensible knowledge representation and reasoning for a family of formalisms known as Description Logics. The approach is based on the notion of adding new concept constructors, and includes a heuristic methodology for specifying the desired extensions, as well as a modularized software architecture that supports implementing extensions. The architecture detailed here falls in the normalize-compared paradigm, and supports both intentional reasoning (subsumption) involving concepts, and extensional reasoning involving individuals after incremental updates to the knowledge base. The resulting approach can be used to extend the reasoner with specialized notions that are motivated by specific problems or application areas, such as reasoning about dates, plans, etc. In addition, it provides an opportunity to implement constructors that are not currently yet sufficiently well understood theoretically, but are needed in practice. Also, for constructors that are provably hard to reason with (e.g., ones whose presence would lead to undecidability), it allows the implementation of incomplete reasoners where the incompleteness is tailored to be acceptable for the application at hand.