Decision supporting system based on fuzzy default reasoning

The work concerns a new formalism of common-sense reasoning modeling. It combines ldquoclassicalrdquo Reiter´s default logic and Brewka´s cumulative default logic with Zadeh´s generalized theory of uncertainty and granular reasoning. Various aspects of uncertainty and ignorance are discussed with respect to intelligent humans´ behavior patterns. The paper introduces basic definitions of Fuzzy Default Logic (FDL) and presents the inference scheme together with the conclusion assessment procedure and problems of hypotheses stability. PROLOG implementation of the entire inference engine is given. The problems of hypotheses generation and revision of beliefs are discussed. Finally, FDL is compared to the answer set programming and other disjunction logic based approaches.