Separating I/O from application logic for rule-based control systems

• Autorzy: Wojnicki I.
• Języki publikacji: EN

Abstrakty

EN

One of the main reasons of using a rule-based approach to program control systems is that they can be formally verified. For such systems communication with the environment is often encoded within the knowledge base. Such inclusion may lead to issues with portability, extendibility, maintainability, and interoperability. The paper proposes a four layer architecture to solve these issues. A proof-of-concept RBS, targeted at control systems, and an example case are also given.

Słowa kluczowe

EN

rule; rule-based; inference; I/O; control system

• Wydawca: AGH University of Science and Technology Press
• Czasopismo: Decision Making in Manufacturing and Services
• Rocznik: 2011
• Tom: Vol. 5, no. 1-2
• Strony: 79--89
• Opis fizyczny: Bibliogr. [10] poz., rys.

Twórcy

autor

Wojnicki I.

• AGH University of Science and Technology, Faculty of Electrical Engineering, Automatics, Computer Science and Electronics, Department of Automatics, al. A. Mickiewicza 30, 30-059 Krakow, Poland

Bibliografia

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• Giarratano, J.C., Gary D. Riley, G.D., 2005. Expert systems: principles and programming Thomson Course Technology.
• Gouyon, J-P., 1994. Kheops users’s guide. Technical Report 92503, Report of Laboratoire d’Automatique et d’Analyse des Systemes, Toulouse, France.
• Jackson, P., 1999. Introduction to Expert Systems. Addison-Wesley, 3rd edition.
• Leś, W., Łosiewicz, M., 2009. The xtt inference engine and the java virtual machine coupling. Master’s thesis, AGH University of Sience and Technology.
• Liebowitz, J. (Ed.), 1998. The Handbook of Applied Expert Systems. CRC Press, Boca Raton.
• Ligęza, A., 2006. Logical Foundations for Rule-Based Systems. Springer-Verlag, Berlin, Heidelberg.
• Nalepa, G.J.,Wojnicki, I., 2007. Proposal of generalized rule programming model. 3rd Workshop on Knowledge Engineering and Software Engineering (KESE 2007) at the 30th annual German conference on Artificial intelligence, September 2007.
• Negnevitsky, M., 2002. Artificial Intelligence. A Guide to Intelligent Systems. Addison-Wesley, Harlow, England; London; New York.