Abstract
In this paper, we argue that logic programming semantics can be more meaningful for abductive reasoning than classical inference by providing examples from the area of knowledge representation and reasoning. The main part of the paper addresses the issue of the computational complexity of the principal decisional problems in abductive reasoning, which are: Given an instance of an abduction problem (i) does the problem have solution (i.e., an explanation); (ii) does a given hypothesis belong to some explanation; and (iii) does a given hypothesis belong to all explanations. These problems are investigated here for the stable model semantics of normal logic programs.
This author was partially supported by the Italian National Research Council under grant 224.07.4/24.07.12; the main part of his work has been carried out while he was visiting the Christian Doppler Lab for Expert System.
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Eiter, T., Gottlob, G., Leone, N. (1995). Complexity results for abductive logic programming. In: Marek, V.W., Nerode, A., Truszczyński, M. (eds) Logic Programming and Nonmonotonic Reasoning. LPNMR 1995. Lecture Notes in Computer Science, vol 928. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-59487-6_1
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