This paper presents a Prolog implementation of a Knowledge-based environment. Although the design is still piecewise, it throws up several issues which are encountered in such systems, including Knowledge representation, integration of the Knowledge base with other simulation tools into a functional architecture, and Knowledge acquisition. The KEMS environment has been under research and development for some time now, and has evolved through four major stepping stones. These have been reported individually in the literature. The first stepping stone involved the implementation of an expert system based on the AI frame paradigm. This expert system formed the core of the simulation environment and was used to generate simulation models for gas compression and servo systems supplied by British Gas who have been collaborators in the project. The second phase involved linking the expert system core to a graphical front-end and a simulator. In the third phase, a Knowledge Acquisition Module (KAM) was implemented to enable domain experts to model systems using a pseudo-natural language format. Finally, KAM was extended to include object-oriented features. The paper contains several applications of the KEMS and KAM prototypes.
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