Abstract
A reason maintenance system which extends an ATMS through Mukaidono's fuzzy logic is described. It supports a problem solver in situations affected by incomplete information and vague data, by allowing nonmonotonic inferences and the revision of previous conclusions when contradictions are detected.
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.Doyle (1979). A Truth Maintenance System. In Artificial Intelligence, 12 (3), pp 231–272.
D.McAllester (1980). An Outlook on Truth Maintenance. In AI Memo 551, AI Lab., MIT, Cambridge (MA).
D.McDermott (1983). Context and Data Dependencies. In A Synthesis, IEEE Trans. Pattern Anal.Mach. Intell., 5 (3), pp. 237–246.
J.de Kleer (1986). An Assumption-based TMS. In Artificial Intelligence, 28 (2), pp. 127–162.
J.P.Martins, S.C.Shapiro (1988). A Model for Belief Revision. In Artificial Intelligence, 35, pp. 25–79.
J.de Kleer, B.C.Williams (1987). Diagnosing Multiple Faults. In Artificial Intelligence, 32, pp. 97–130.
B.Falkenheiner (1988). Towards a General Purpose Belief Maintenance System. In J.F.Lemmer, L.N.Kanal (eds.) Uncertainty in Artificial Intelligence: 2nd Conference, North-Holland, pp.125–132.
B.D'Ambrosio (1989). A Hybrid Approach to Reasoning Under Uncertainty. In L.N.Kanal, T.S.Levitt, J.F.Lemmer (eds.) Uncertainty in Artificial Intelligence: 3rd Conference, North-Holland, pp.267–283.
G.M. Provan (1989). An Analysis of ATMS-based Techniques for Computing Dempster-Shafer Belief Functions. In Proceedings of the.9th IJCAI, Detroit Aug. 1989, pp. 1115–1120.
K.B.Laskey, P.E. Lehner(1989). Assumptions, Beliefs and Probabilities. In Artificial Intelligence 41, pp. 65–77.
D.Dubois, J.Lang, H.Prade (1990). Handling Uncertain Knowledge in an ATMS Using Possibilistic Logic. In Proceeding of ECAI Workshop on Truth Maintenance Systems, Stockolm.
J.A.Robinson (1965). A Machine-oriented Logic Based on the Resolution Principle. In Journal of ACM, 12 (1), pp. 23–41.
R.C.T.Lee (1972). Fuzzy Logic and the Resolution Principle. In Journal of ACM, 19 (1), pp.109–119.
M.Mukaidono (1982). Fuzzy Inference of Resolution Style. In R.R.Yager (Ed.) Fuzzy Set and Possibility Theory, Pergamon Press, New York, pp. 224–231.
M.Mukaidono, Z. Shen, L. Ding (1989). Fundamentals of Fuzzy Prolog. In International Journal of Approximate Reasoning, 3, pp. 179–193.
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© 1991 Springer-Verlag Berlin Heidelberg
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Fringuelli, B., Marcugini, S., Milani, A., Rivoira, S. (1991). Truth maintenance in approximate reasoning. In: Ardizzone, E., Gaglio, S., Sorbello, F. (eds) Trends in Artificial Intelligence. AI*IA 1991. Lecture Notes in Computer Science, vol 549. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-54712-6_256
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DOI: https://doi.org/10.1007/3-540-54712-6_256
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