Title :
ALCMEN: a language for qualitative/quantitative knowledge representation in expert supervisory process control
Author :
Martin, Joseph Aguilar ; Desroches, Philippe ; Thomas-Baudin, Veronique
Author_Institution :
LAAS-CNRS, Toulouse, France
Abstract :
ALCMEN (automaticians language for causal modelisation for expert knowledge) is a language capable to handle simultaneously imprecision and uncertainty, and precise equations, in order to solve the communication problem between process experts and control engineers. ALCMEN appears as a network of interconnected blocks and a list of structured variables. It captures the causal influence of a cause on an effect and provides the possibility of parametrizing that relation by one or many conditions. Each causal relation, is described according to the most explicit available knowledge, either using equations or natural language. Specification methodology is also provided using real time expert system development language G2
Keywords :
knowledge representation; process computer control; specification languages; ALCMEN; G2; causal relation; expert supervisory process control; knowledge representation; language specification; numeric symbolic interface; qualitative simulation; real time expert system development language; Automatic control; Communication system control; Equations; Expert systems; Knowledge engineering; LAN interconnection; Natural languages; Process control; Real time systems; Uncertainty;
Conference_Titel :
AI, Simulation and Planning in High Autonomy Systems, 1991. Integrating Qualitative and Quantitative System Knowledge, Proceedings of the Second Annual Conference on
Conference_Location :
Cocoa Beach, FL
Print_ISBN :
0-8186-2162-1
DOI :
10.1109/AIHAS.1991.138452