Abstract

An approach to integration of methods of constraint programming with various knowledge representation means, such as frames, semantic networks, and production rules, is considered. A knowledge representation language developed on the basis of this approach is presented. In contrast to other languages that also use the constraint programming technique, this language allows us to operate with imprecisely defined (subdefinite) values and to change the initial set of constraints. The language based on the proposed approach can be used for developing intelligent systems which require the combination of logical inference and computations over imprecise values.

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Issue
Pages
58-61