Abstract
Symbolic reasoning systems have leveraged propositional logic frameworks to build diagnostics tools capable of describing complex artifacts, while also allowing for a controlled and efficacious search over failure modes. These diagnostic systems represent a complex and varied context in which to explore general intelligence. This paper explores the application of a different reasoning system to such frameworks, specifically, the Non-Axiomatic Reasoning System. It shows how statements can be built describing an artifact, and that NARS is capable of diagnosing abnormal states within examples of said artifact.
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References
Brusoni, V., Console, L., Terenziani, P., Dupré, D.T.: A spectrum of definitions for temporal model-based diagnosis. Artif. Intell. 102(1), 39–79 (1998)
Ceriani, L., Zanella, M.: Model-based diagnosis and generation of hypothesis space via AI planning. In: 25th International Workshop on the Principles of Diagnosis (DX-14) (2014)
Console, L., Torasso, P.: A spectrum of logical definitions of model-based diagnosis1. Comput. Intell. 7(3), 133–141 (1991)
De Kleer, J.: An assumption-based TMS. Artif. Intell. 28(2), 127–162 (1986)
Felfernig, A., Friedrich, G., Jannach, D., Stumptner, M.: Consistency-based diagnosis of configuration knowledge bases. Artif. Intell. 152(2), 213–234 (2004)
Hammer, P., Lofthouse, T., Wang, P.: The OpenNARS implementation of the non-axiomatic reasoning system. In: Steunebrink, B., Wang, P., Goertzel, B. (eds.) AGI -2016. LNCS (LNAI), vol. 9782, pp. 160–170. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-41649-6_16
ohan de Kleer, J., Williams, B.C.: Diagnosis with behavioral modes. Proc. IJ CAI 1(989), 1324–1330 (1989)
de Kleer, J., Williams, B.C.: Diagnosing multiple faults. Artif. Intell. 32(1), 97–130 (1987)
Koitz, R., Wotawa, F.: SAT-based abductive diagnosis. In: International Workshop on Principles of Diagnosis, vol. 26, p. 10 (2015)
McCarthy, J.: Applications of circumscription to formalizing common-sense knowledge. Artif. Intell. 28(1), 89–116 (1986)
Peng, Y., Reggia, J.A.: Abductive Inference Models for Diagnostic Problem-Solving. Springer, New York (2012). https://doi.org/10.1007/978-1-4419-8682-5
Reiter, R.: A theory of diagnosis from first principles. Artif. Intell. 32(1), 57–95 (1987)
ten Teije, A., van Harmelen, F.: An extended spectrum of logical definitions for diagnostic systems. In: Proceedings of DX-94 Fifth International Workshop on Principles of Diagnosis, pp. 334–342 (1994)
Wang, P.: Rigid Flexibility: The Logic of Intelligence. Springer, Dordrecht (2006). https://doi.org/10.1007/1-4020-5045-3
Wang, P.: Non-Axiomatic Logic: A Model of Intelligent Reasoning. World Scientific, Singapore (2013)
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Power, B., Li, X., Wang, P. (2019). Generalized Diagnostics with the Non-Axiomatic Reasoning System (NARS). In: Hammer, P., Agrawal, P., Goertzel, B., Iklé, M. (eds) Artificial General Intelligence. AGI 2019. Lecture Notes in Computer Science(), vol 11654. Springer, Cham. https://doi.org/10.1007/978-3-030-27005-6_16
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DOI: https://doi.org/10.1007/978-3-030-27005-6_16
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