| O.Arieli and A.Avron. A bilattice-based approach to recover consistent data from inconsistent knowledgebases. Proc. 4th Bar-Ilan Symp. on Foundations of AI, (M.Koppel and E.Shamir, eds.), pages 14--23. AAAI Press, 1995. |
....noted before, a drawback of using maximal consistent subsets is that none of these sets necessarily corresponds to the intended semantics of the original information. An approach that salvages consistent data from polluted knowledge bases and still preserves their semantics is presented in [1, 2]. In what follows we briefly review this method and in the next section we generalize it for prioritized knowledge bases. Definition 2.5 A model M of a set of clauses KB is consistent if Inc M (KB) A knowledge base is consistent if is has a consistent model. Proposition 2.6 A ....
....sets of KB. These sets are associated with the (most consistent) models fp : t; q : g and fp : q : tg, respectively. Note that S 1 is no longer a recovered set of KB 0 =KB [ f:pg, since there is no consistent model of S 1 that is expandable to a model of KB 0 . Proposition 2. 10 [1, 2] Every set that is associated with a model of KB is a recovered set of KB. Given an inconsistent knowledge base, the idea is to choose one of its maximal recovered sets (see [2] and to treat this set as the relevant knowledge base for deducing classical inferences. As the following proposition ....
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O.Arieli and A.Avron. A bilattice-based approach to recover consistent data from inconsistent knowledgebases. Proc. 4th Bar-Ilan Symp. on Foundations of AI, (M.Koppel and E.Shamir, eds.), pages 14--23. AAAI Press, 1995.
....mcem of KB, but now it is also the single element of kmin(KB) therefore KB j= kmin :q. Several consequence relations similar to j= mcem are considered in the literature. Priest [Pr91] uses a similar consequence relation j= LPm for defining the logic LPm from the three valued logic LP. In [AA95] it is shown that j= mcem and j= Omega are the same in case Exact = The proof there applies in the general case as well. Therefore, when switching to four valued semantics and using only the k minimal mcems, one might consider fewer models than in the case of LPm, since for every k minimal ....
O.Arieli, A.Avron. A bilattice-based approach to recover consistent data from inconsistent knowledge-bases. Proc. of the 4th Bar-Ilan Symp. on Foundations of Artificial Intelligence (BISFAI'95), pp. 231-240; 1995.
....point of view, however, this leaves something to be desired. Drawing any conclusion whatsoever just because of the existence of a contradiction, is certainly unrealistic, e.g. in knowledge bases in which the information comes from several sources. A preliminary version of this paper appears in [AA95]. One possible solution to this problem is to use some kind of a paraconsistent logic ( dC74] i.e. a logic in which trivial reasoning from a contradiction is not allowed. Several candidates has been suggested in the literature (see, e.g. BCDLP, BDP95, CSHL, KL92, Lo94, Pr89, Pr91, Su90a, ....
O.Arieli, A.Avron. A bilattice-based approach to recover consistent data from inconsistent knowledge-bases. Proc. of the 4th Bar-Ilan Symp. on Foundations of Artificial Intelligence (BISFAI'95). AAAI Press pp.14--23, 1995.
....KB remain the same, while M 1 becomes the single k minimal exact model of KB, so now KB j= kmin :q. Several consequence relations similar to j= mcem are considered in the literature. Priest [Pr91] uses similar consequence relation for defining the logic LPm from the threevalued logic LP. Now, in [AA95] it is shown that for finite sets of assertions j= mcem and j= Omega are the same. Therefore, when switching to four valued semantics and using only the k minimal mcems, one might consider fewer models than in the case of LPm, since for every k minimal mcem that assigns to an atomic formula ....
O.Arieli, A.Avron. A bilattice-based approach to recover consistent data from inconsistent knowledge-bases. Proc. 4th Bar-Ilan Symp. on Foundations of Artificial Intelligence (BISFAI'95), pp.231-240; 1995.
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