Knowledge representation with granular attributive logic for XTT-based expert systems

This paper presents an extension of classical attributive logic using atomic values of attributes. In the proposed logic set values are allowed and various relational symbols are used to form atomic formulae. The proposed language provides a concise and elegant tool for design, implementation and verification of rule-based systems