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TFL: an algebraic language to specify the dynamic behaviour of knowledge-based systems

Published online by Cambridge University Press:  07 July 2009

Christine Pierret-Golbreich  and
Xavier Talon
Christine Pierret-Golbreich
Affiliation:
L.R.I. CNRS URA 410, Université Paris Sud, 91405 Orsay Cedex, France (Email):[pierret, talon] @lri.fr
Xavier Talon
Affiliation:
L.R.I. CNRS URA 410, Université Paris Sud, 91405 Orsay Cedex, France (Email):[pierret, talon] @lri.fr
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Abstract

TFL, the Task Formal Language, has been developed for integrating the static and dynamic aspects of knowledge based systems. This paper focuses on the formal specification of dynamic behaviour. Although fundamental in knowledge based systems, strategic reasoning has been rather neglected until now by the existing formal specifications. Most languages were generally more focused on the domain and problem-solving knowledge specification than on the control. The formalisation presented here differs from previous ones in several aspects. First, a different representation of dynamic knowledge is proposed: TFL is based on Algebraic Data Types, as opposed to dynamic or temporal logic. Second, dynamic strategic reasoning is emphasised, whereas existing languages only offer to specify algorithmic control. Then, TFL does not only provide the specification of the problem-solving knowledge of the object system, but also of its strategic knowledge. Finally, the dynamic knowledge of the meta-system itself is also specified. Moreover, modularisation is another important feature of the presented language.

Type
Research Article
Information
The Knowledge Engineering Review , Volume 11 , Issue 3 , September 1996 , pp. 253 - 280
Copyright
Copyright © Cambridge University Press 1996

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References

Aben, M, 1993. “Formally specifying reusable knowledge model components” Knowledge Acquisition 5 119–141.CrossRefGoogle Scholar
Aben, M, 1995. Formal methods in knowledge engineering. PhD thesis, Universiteit van Amsterdam.Google Scholar
Albert, P, Corby, O, Gobinet, P and Neveu, B, 1992. Langage de spécification de la communication et du contrôle dans un blackboard, Rapport intermédiaire No III.1 du contrat l.91.E117, DRET-ILOG-INRIA.Google Scholar
Aitken, S, Reichgelt, H and Shadbolt, N, 1992. Representing KADS models in QI. Technical report, Al Group, 05 27–31, University of Nottingham.Google Scholar
Breuker, J and Van de Velde, W, 1994. Common KADS Library for Expertise Modelling. IOS Press.Google Scholar
Bidiot, M, 1989. Pluss, un langage pour le développement de spécifications algébriques modulaires. PhD thesis, Université de Paris-Sud.Google Scholar
Brachman, RJ and Schmolze, JG, 1985. An overview of the KL-ONE knowledge representation system. Cognitive Science 9 171–216.Google Scholar
Capy, F, 1987. ASSPEGIQUE: un environnement d'exeptions… Une semantique operationnelle des eralgebres, formalisme prenant en compte les exeptions. un environnement integre de specification algebrique: asspegique. PhD thesis, Université Paris-Sud.Google Scholar
Chandrasekaran, B, 1988. Generic tasks as building blocks for knowledge-based-reasoning: the diagnosis and routine design exemples. Knowledge Engineering Review 3 (3).Google Scholar
McDermott, J, 1988. Preliminary steps towards a taxinomy of problem solving methods. In: Marcus, S., (ed.), Automating Knowledge Acquisition for Expert Systems, 225–255, Kluwer Academic.CrossRefGoogle Scholar
Fensel, D, Angele, J and Landes, D, 1991. “A knowledge acquisition and representation languages”. In: Proc. Expert Systems and their Applications, 11th International Workshop, Conference Tools, Techniques and Methods, Avignon, France, 05 27–31.Google Scholar
Fensel, D, 1995. “Formal specification languages in knowledge and software engineering”. The Knowledge Engineering Review 10 (4) 361–404, 12.CrossRefGoogle Scholar
Fensel, D, 1995. The Knowledge Acquisition and Representation Language KARL, Kluwer Academic.CrossRefGoogle Scholar
Fensel, D and van Harmelen, F, 1994. “A comparison of langages which operationalise and formalise KADS models of expertise”. The Knowledge Engineering Review.CrossRefGoogle Scholar
Gaudel, MC, 1884. “A first introduction to PLUSS”. In: METEOR Report, 493–510, 12.Google Scholar
Gaudel, MC, 1985. “Towards structured algebraic specifications”. In ESPRIT'85 Status Report, North Holland, 09 23–25.Google Scholar
Gaudel, MC, 1990. Algebraic specifications. Rapport 557, LRI, University Paris Sud.Google Scholar
Gaudel, MC, 1994. “Formal specification techniques, invited state-of-the-art report, extended abstract”. In: IEEE-ACM International Conference on Software Engineering, 223–227.Google Scholar
Gaudel, MC, 1992. “Test selection based on ADT specification”. In: IWPT92, Wiley.Google Scholar
Harel, D, 1984. Handbook of Philosophical Logic, volume II: Extensions of Classical Logic, Chapter “Dynamic Logic”, Reidel.Google Scholar
Van, Harmelen F and Balder, F, 1992. “(ML)2: A formal language for KADS models of expertise”. Knowledge Acquisition 4 127–161.Google Scholar
Hayes-Roth, B, 1985. “A blackboard architecture for control”. Artificial Intelligence 26 251–321.CrossRefGoogle Scholar
Jonker, W and Spee, J, 1992. “Yet another formalisation of KADS conceptual models”. In: Wetter, Tet al. (eds), Proceedings of the 6th European Knowledge Acquisition for Knowledge-Based Systems Workshop (EKA W-92), 211–229.CrossRefGoogle Scholar
Kaplan, S, 1987. Spécification algébrique de types de données à accès concurrent. PhD thesis, Université de Paris-Sud.Google Scholar
Linster, M, Karbach, W, Voβ, A and Walther, J, 1992. “An analysis of the role of operational modelling languages in the development of knowledge-based systems”. In: Proceedings of the 2nd Japaneses Knowledge Acquisition for Knowledge-Based Systems Workshop, Hatayoama, Japan.Google Scholar
Marre, B, 1991. “Toward automatic test data set selection using algebraic specifications and logic programming”. In: Proceedings of the Eighth International Conference, 202–221, MIT Press.Google Scholar
Marre, B, 1991. Une méthode et un outil d'assistance a la sélection de jeux de tests à partir de spécifications algébriques. PhD thesis, Université de Paris-Sud.Google Scholar
Musen, MA, 1989. Automated Generation of Model-Based Knowledge-Acquisition Tools. Research Notes in Artificial Intelligence, Pitman.Google Scholar
Newell, A, 1982. “The knowledge level”. Artificial Intelligence 18 35–418, 87–1273.CrossRefGoogle Scholar
Orejas, F, Navarro, M and Sanchez, A, 1992. Algebraic implementation of abstract data types: a survey. In: Proceedings 8 WADT 3rd COMPASS Workshop, Dourdan, FranceGoogle Scholar
Pierret-Golbreich, C, 1994. “Task model: a framework for the design of models of expertise and their operationalization”. In: Proceedings Knowledge Acquisition Workshop, Banf, Canada.Google Scholar
Pierret-Golbreich, C., 1996. “Correction of methods w.r.t problems specifications”. In: ECAI-96 Workshop “Validation, Verfication and Refinements of KBS”.Google Scholar
Pierret-Golbreich, C, 1996. “Modular and reusable specifications in knowledge engineering: formal specification of goals and their development”. In: 6th Workshop on Knowledge Engineering Methods and Languages, Paris, France.Google Scholar
Pierret-Golbreich, C and Talon, X, 1994. “Specifications formelles des connaissances pour l'acquisition: une approche basée sur les types abstraits algébriques”. Unpublished.Google Scholar
Steels, L, 1990. “Components of expertise”. AI Magazine.Google Scholar
Terry, A, 1983. “The crysalis project: Hierarchical control of production systems. Technical Report HPP–83– 19, Stanford University.Google Scholar
Treur, J and Wetter, T, 1993. Formal Specification of Complex Reasoning Systems. Ellis Horwood.Google Scholar
van, Langevelde IA, Philipsen, AW and Treuer, J, 1992. “Formal specification of compositional architectures”. In: Proceedings of the 10th European Conference, ECAI'92, 272–276, Wiley.Google Scholar
van, Harmelen F and Fensel, D, 1995. “Formal methods in knowledge engineering”. The Knowledge Engineering Review 10 (4) 345–360, 12.Google Scholar
van Langevelde, I, Philipsen, A and Treur, J, 1992. “Formal specification of compositional architectures”. In: Proceedings of the 10th European Conference on Artifical Intelligence (ECAI 92), Vienna, Austria.Google Scholar
van Langevelde, I, Philipsen, A and Treur, J, 1993. “Formal specification of complex reasoning systems” In: A Compositional Architecture For Simple Design Formally Specified in DESIRE, Ellis Horwood.Google Scholar
Wielinga, B, Van, de Velde W, Schreiber, G and Akkermans, H, 1993. Expertise Model Definition Document, University of Amsterdam.Google Scholar
Wetter, T and Schmidt, W, 1991. “Formalisation of the KADS interpretation models”. In: Proceedings of the 8th Conference of the Society for the Study of Artificial Intelligence and Simulation of Behavior (AISB'91), Springer-Verlag.Google Scholar
Wielinga, B, Schreiber, G and Breuker, J, 1992. “KADS: A modelling approach to knowledge engineering”. Knowledge Acquisition Journal 4 (1) 1–162.Google Scholar