| O.Arieli, Four-valued logics for reasoning with uncertainty in prioritized data, in: Information, Uncertainty, Fusion, eds. B.Bouchon-Meunier, R.R.Yager and L.A.Zadeh, Kluwer Academic Publishers, 1999, pp. 293-304. |
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O.Arieli, Four-valued logics for reasoning with uncertainty in prioritized data, in: Information, Uncertainty, Fusion, eds. B.Bouchon-Meunier, R.R.Yager and L.A.Zadeh, Kluwer Academic Publishers, 1999, pp. 293-304.
.... for dealing with this task are based on techniques of belief revision [31] methods of resolving contradictions by quantitative considerations (such as majority vote [32] or qualitative ones (e.g. de ning priorities on di erent sources of information or preferring certain data over another [4, 9]) and approaches that are based on rewriting rules for representing the information in a speci c form [25] As in our case, abduction is used for database updating in [28] and an extended form of abduction is used in [26, 39] to explain modi cations in a theory. The use of three valued logics ....
O.Arieli. Four-valued logics for reasoning with uncertainty in prioritized data. In: Information, Uncertainty, Fusion, B.Bouchon-Meunier, R.R.Yager, L.Zadeh, editors, pp.263-309, Kluwer, 1999.
.... for dealing with this task are based on techniques of belief revision [20] methods of resolving contradictions by quantitative considerations (such as majority vote [21] or qualitative ones (e.g. de ning priorities on di erent sources of information or preferring certain data over another [2, 4, 5]) Other approaches are based on rewriting rules for representing the information in a speci c form [14] or use multiple valued semantics (e.g. annotated logic programs [28, 29] and bilattice based formalisms [12, 22] together with non classical refutation procedures [11, 19, 28] that allow to ....
O.Arieli. Four-valued logics for reasoning with uncertainty in prioritized data. In: Information, Uncertainty, Fusion, 263-309, Kluwer, 1999.
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