Building expert systems
| Hi-index | 0.00 |
The paper presents a novel expert system architecture which supports explicit representation and effective use of both declarative and procedural knowledge. These two types of expert knowledge are represented by means of production rules and event-graphs respectively, and they are processed by a unified inference engine. Communication between the rule level and the event-graph level is based on a full visibility of each level on the internal state of the other, and it is structured in such a way as to allow each level to expert control on the other. This structure offers several advantages over more traditional architectures. Knowledge representation is more natural and transparent; knowledge acquisition turns out to be easier as pieces of knowledge can be immediately represented without the need of complex transformation and restructuring; inference is more effective due to reduced non-determinism resulting from explicit representation of fragments of procedural knowledge in event-graphs; finally, explanations are more natural and understandable. The proposed architecture has been adopted for the design of PROP, an expert system for on-line monitoring of the cycle water pollution in a thermal power plant. PROP is running on a SUN-2 workstation and has been tested on a sample of real cases.