A relational model for knowledge representation in expert systems

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Abstract

This paper presents a relational model for representation and utilization of declarative knowledge. First, we identify names as the essential notion to represent concepts; a taxonomy and semantic interpretation of concept names is given. Then we express the knowledge base in first-order logic as a collection of Horn clauses and analyze the volume of solutions space limited by the total number of rules known to the expert system and depending on the rules structure. Finally, a relational model for effective building of expert systems is presented; we introduce addresses between names and routes as logical bridges through which the rules send and receive information. The idea behind this model is an active use of the constraints to prune the search space a priori by removing combinations of values that cannot appear together in a solution. This model is an attempt to solve efficiently, inside logic programming, those problems that can be expressed as constraint satisfaction problems. Its relational form makes it convenient for stating concepts; its addresses are oriented to avoid failures and do not try to recover from failures. This model is general enough to permit significant reduction of the necessary computations in the solutions space by using domains of concepts and handling constraints to avoid redundant works and bad backtracking choices.

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