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Reasoning in Inconsistent Knowledge Bases
February 1995 (vol. 7 no. 1)
pp. 177-189

Abstract—Databases and knowledge bases could be inconsistent in many ways. For example, during the construction of an expert system, we may consult many different experts. Each expert may provide us with a group of rules and facts which are self-consistent. However, when we coalesce the facts and rules provided by these different experts, inconsistency may arise. Alternatively, knowledge bases may be inconsistent due to the presence of some erroneous information. Thus, a framework for reasoning about knowledge bases that contain inconsistent information is necessary. Such a framework was described in [1], [21]. However, existing frameworks for reasoning with inconsistency do not support reasoning by cases and reasoning with the law of excluded middle (everything is either true or false). In this paper, we show how reasoning with cases, and reasoning with the law of excluded middle may be captured. We develop a declarative and operational semantics for knowledge bases that are possibly inconsistent. We compare and contrast our work with work on explicit and non-monotonic modes of negation in logic programs and suggest under what circumstances one framework may be preferred over another.

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Index Terms:
Logic programming, deductive databases, reasoning with inconsistency, nonmonotonic negation.
Citation:
John Grant, V.s. Subrahmanian, "Reasoning in Inconsistent Knowledge Bases," IEEE Transactions on Knowledge and Data Engineering, vol. 7, no. 1, pp. 177-189, Feb. 1995, doi:10.1109/69.368510
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