Description Logics with Fuzzy Concrete Domains
This work addresses the need for handling uncertainty in knowledge representation for AI applications, but it appears incremental as it extends existing description logics with fuzzy concepts.
The authors tackled the problem of representing and reasoning with vague or imprecise data in description logics by introducing a fuzzy version with concrete domains, resulting in a reasoning algorithm that combines completion rules with bounded mixed integer programming.
We present a fuzzy version of description logics with concrete domains. Main features are: (i) concept constructors are based on t-norm, t-conorm, negation and implication; (ii) concrete domains are fuzzy sets; (iii) fuzzy modifiers are allowed; and (iv) the reasoning algorithm is based on a mixture of completion rules and bounded mixed integer programming.