Abstract
The ability to select suitable diagnostic assumptions and models extends the power of model-based diagnosis for complex systems and can explicitly be modeled by diagnostic strategies. Recently, Nejdl, Fröhlich and Schroeder have developed a framework, which allows to express these strategies as formulas of a meta-language. This paper presents a method for designing strategy knowledge bases as well as an efficient straightforward operational semantics for exploiting them.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
C. Böttcher and O. Dressler. Diagnosis process dynamics: Holding the diagnostic trackhound in leash. In IJCAI93, pages 1460–1471. Morgan Kaufmann Publishers, Inc., 1993.
C. Böttcher and O. Dressler. A framework for controlling model-based diagnosis systems with multiple actions. Annals of Mathematics and Artificial Intelligence, 11(1–4), 1994.
R. Davis. Diagnostic reasoning based on structure and behaviour. Artificial Intelligence, 24:347–410, 1984.
J. de Kleer, O. Raiman, and M. Shirley. One step lookahead is pretty good. In Second International Workshop on the Principles of Diagnosis, Milano, Italy, October 1991.
J. de Kleer and B. C. Williams. Diagnosing multiple faults. Artificial Intelligence, 32:97–130, 1987.
C. V. Damásio, L. M. Pereira, and W. Nejdl. Revise: An extended logic programming system for revising knowledge bases. In KRR94, pages 607–618, Bonn, Germany, 1994. Morgan Kaufmann Publishers, Inc.
O. Dressler and P. Struss. Back to defaults: Characterizing and computing diagnoses as coherent assumption sets. In ECAI92, pages 719–723, 1992.
P. Fröhlich, W. Nejdl, and M. Schröder. A formal semantics for preferences and strategies in model-based diagnosis. In 5th International Workshop on Principles of Diagnosis (DX-94), pages 106–113, New Paltz, NY, 1994.
M. R. Genesereth. The use of design descriptions in automated diagnosis. Artificial Intelligence, 24:411–436, 1984.
Walter C. Hamscher. Modeling digital circuits for troubleshooting. Artificial Intelligence, 51(1–3):223–271, October 1991.
The iscas-85 benchmark archive. Accessible via anonymous ftp from ftp.mcnc.org, 1985.
Igor Mozetič. Hierarchical model-based diagnosis. International Journal of Man-Machine Studies, 35:329–362, 1991.
W. Nejdl, P. Fröhlich, and M. Schroeder. A formal framework for representing diagnosis strategies in model-based diagnosis systems. In IJCAI95, pages 1721–1727, 1995. Morgan Kaufmann Publishers, Inc.
Raymond Reiter. A theory of diagnosis from first principles. Artificial Intelligence, 32:57–95, 1987.
P. Struss and O. Dressler. Physical negation — Integrating fault models into the general diagnostic engine. In IJCAI89, pages 1318–1323, Morgan Kaufmann Publishers, Inc.
P. Struss. Diagnosis as a process. In W. Hamscher, L. Console, and J. de Kleer, editors, Readings in Model-Based Diagnosis, pages 408–418. Morgan Kaufmann Publishers, Inc., 1992.
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1996 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Fröhlich, P., Nejdl, W., Schroeder, M. (1996). Design and implementation of diagnostic strategies using modal logic. In: Alferes, J.J., Pereira, L.M., Orlowska, E. (eds) Logics in Artificial Intelligence. JELIA 1996. Lecture Notes in Computer Science, vol 1126. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61630-6_7
Download citation
DOI: https://doi.org/10.1007/3-540-61630-6_7
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-61630-6
Online ISBN: 978-3-540-70643-4
eBook Packages: Springer Book Archive