Abstract

This chapter will discuss the implementation of the reasoning services which form the core of DL-based knowledge representation systems. To be useful in realistic applications, such systems need both expressive logics and fast reasoners. As expressive logics inevitably have high worst-case complexities, this can only be achieved by employing highly optimized implementations of suitable reasoning algorithms. Systems based on such implementations have demonstrated that they can perform well with problems that occur in realistic applications, including problems where unoptimized reasoning is hopelessly intractable.

Introduction

The usefulness of Description Logics in applications has been hindered by the basic conflict between expressiveness and tractability. Realistic applications typically require both expressive logics, with inevitably high worst-case complexities for their decision procedures, and acceptable performance from the reasoning services. Although the definition of acceptable may vary widely from application to application, early experiments with Description Logics indicated that, in practice, performance was a serious problem, even for logics with relatively limited expressive powers [Heinsohn et al., 1992].

On the other hand, theoretical work has continued to extend our understanding of the boundaries of decidability in Description Logics, and has led to the development of sound and complete reasoning algorithms for much more expressive logics. The expressive power of these logics goes a long way towards addressing the criticisms leveled at Description Logics in traditional applications such as ontological engineering [Doyle and Patil, 1991] and is sufficient to suggest that they could be useful in several exciting new application domains, for example reasoning about database schemas and queries [Calvanese et al., 1998f; 1998a] and providing reasoning support for the so-called Semantic Web [Decker et al., 2000; Bechhofer et al., 2001b].