Approximating Defeasible Logics to Improve Scalability

Defeasible rules are used in providing computable representations of legal documents and, more recently, have been suggested as a basis for explainable AI. Such applications draw attention to the scalability of implementations. The defeasible logic DL(partial||) was introduced as a more scalable alternative to DL(partial), which is better known. In this paper we consider the use of (implementations of) DL(partial||) as a computational aid to computing conclusions in DL(partial) and other defeasible logics, rather than as an alternative to DL(partial). We identify conditions under which DL(partial||) can be substituted for DL(partial) with no change to the conclusions drawn, and conditions under which DL(partial||) can be used to draw some valid conclusions, leaving the remainder to be drawn by DL(partial).