Learning to Control Inconsistent Knowledge
نویسندگان
چکیده
We claim that knowledge can be "naturally" inconsistent in some domains such as those involving multi-criteria optimization. So rather than avoiding inconsistency , our concern is to cope with it. This paper presents a technique inspired from inductive learning, to achieve this aim : from an inconsistent set of rules and a set of examples, metarules are learned to solve the contradictions among the previous rules. This approach requires the initial inconsistent rules to be redundant enough, no matter how erroneous.
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تاریخ انتشار 1992