Prototyping Rule-Based Expert Systems with the Aid of Model Transformations

Abstract

The problem of improving efficiency of intelligence systems engineering remains a relevant topic of scientific research. One of the trends in this area is the use of the principles of cognitive (visual) modelling and design as well as approaches based on generative programming and model transformations. This paper aims to describe the implementation and application of model transformations for prototyping rule-based knowledge bases and expert systems. The implementation proposed uses the main principles of the Model Driven Architecture (MDA) (e.g., model types and creation stages) and considers the features of developing intelligent systems. Therefore, the current research employs the following tools: Ontologies for the representation of the computation-independent model; the author’s original notation, namely, the Rule Visual Modelling Language (RVML) to create the platform-independent and platform-specific models; the C Language Integrated Production System (CLIPS) and the Drools Rule Language (DRL) as the programming languages (as the platforms). The approach proposed targets non-programmers (domain experts and analytics) and makes the design process of rule-based expert systems and knowledge bases more efficient. The paper also presents a detailed description of the main elements of the approach including models, transformations and a specialised software (Personal Knowledge Base Designer).