RuleRS: a rule-based architecture for decision support systems

Abstract

Decision-makers in governments, enterprises, businesses and agencies or individuals, typically, make decisions according to various regulations, guidelines and policies based on existing records stored in various databases, in particular, relational databases. To assist decision-makers, an expert system, encompasses interactive computer-based systems or subsystems to support the decision-making process. Typically, most expert systems are built on top of transaction systems, databases, and data models and restricted in decision-making to the analysis, processing and presenting data and information, and they do not provide support for the normative layer. This paper will provide a solution to one specific problem that arises from this situation, namely the lack of tool/mechanism to demonstrate how an expert system is well-suited for supporting decision-making activities drawn from existing records and relevant legal requirements aligned existing records stored in various databases.We present a Rule-based (pre and post) reporting systems (RuleRS) architecture, which is intended to integrate databases, in particular, relational databases, with a logic-based reasoner and rule engine to assist in decision-making or create reports according to legal norms. We argue that the resulting RuleRS provides an efficient and flexible solution to the problem at hand using defeasible inference. To this end, we have also conducted empirical evaluations of RuleRS performance.