Approximating Defeasible Logics to Improve Scalability
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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(∂_||) was introduced as a more scalable alternative to DL(∂), which is better known. In this paper we consider the use of (implementations of) DL(∂_||) as a computational aid to computing conclusions in DL(∂) and other defeasible logics, rather than as an alternative to DL(∂). We identify conditions under which DL(∂_||) can be substituted for DL(∂) with no change to the conclusions drawn, and conditions under which DL(∂_||) can be used to draw some valid conclusions, leaving the remainder to be drawn by DL(∂).
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