KNOWLEDGE REPRESENTATION AND INFERENCE FOR ANALYSIS AND DESIGN OF DATABASES AND TABULAR RULE-BASED SYSTEMS

Abstract

Rulc-based Systems constitute a powerful tool for speciftcation of knowledge in design and implementation of knowledge-based Systems. They provide also a universal programming paradigm for domains such as intelligent control, decision support, situation classification and opcrational knowledge encoding. In order to assure safe and reliable performance, such Systems should satisfy certain format reąuirements, including completeness and consistency. This paper addresses the issue of analysis and verification of selected properties of a class of such Systems in a systematic way. A uniform, tabular scheme of single-levcl rule-bascd Systems is considered. Such systcms can be applied as a generalized form of databases for speciftcation of data pattems (unconditional knowledge), or can be used for deftning attributive decision tables (conditional knowledge in form of rules). They can also serve as lower-level componcnts of a hierarchical, multi-lcvcl control and decision support knowledge-based systcms. An algebraic knowledge rcprescntation paradigm using extcnded tabular rcprcsentation, similar to relational databasc tables is prcsentcd and algebraic bascs for system analysis, vcrification and design support arc outlined