Intelligent Tableau Algorithm for DL Reasoning

Abstract

Although state-of-the-art description logic (DL) reasoners are equipped with a comprehensive set of optimizations, reasoning performance is still a major bottleneck in both research and real world applications. In this paper, we propose a sound and complete algorithm called the intelligent tableau algorithm by incorporating comprehensive learning techniques to tackle all DL reasoning tasks. We also provide a reference implementation reasoner called LIGHT for the DL ${\cal ALC}$ dialect based on the algorithm we developed. Preliminary tests indicate that significant improvements can be achieved, i.e., compared to other state-of-the-art reasoners, LIGHT is up to two orders of magnitude faster for simple problems and several orders of magnitude faster for more difficult problems. Even though in this work our discussion is restricted to the ${\cal ALC}$ reasoning problem, our conjecture is that the algorithm developed can easily be extended to super-logics of ${\cal ALC}$.