Approximate Model-Based Diagnosis Using Greedy Stochastic Search

  • Alexander Feldman
  • Gregory Provan
  • Arjan van Gemund
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4612)


Most algorithms for computing diagnoses within a model-based diagnosis framework are deterministic. Such algorithms guarantee soundness and completeness, but are NP-hard. To overcome this complexity problem, we propose a novel approximation approach for multiple-fault diagnosis, based on a greedy stochastic algorithm called Safari (StochAstic Fault diagnosis AlgoRIthm). Safari sacrifices guarantees of optimality, but for models in which component failure modes are defined solely in terms of a deviation from nominal behavior (known as weak fault models), it can compute 80-90% of all cardinality-minimal diagnoses, several orders of magnitude faster than state-of-the-art deterministic algorithms. We have applied this algorithm to the 74XXX and ISCAS-85 suites of benchmark combinatorial circuits, demonstrating order-of-magnitude speedup over a well-known deterministic algorithm, CDA*, for multiple-fault diagnoses.


Fault Diagnosis Fault Model Consistency Check Deterministic Algorithm Single Fault 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Reiter, R.: A theory of diagnosis from first principles. Artificial Intelligence 32(1), 57–95 (1987)zbMATHCrossRefGoogle Scholar
  2. 2.
    Bylander, T., Allemang, D., Tanner, M., Josephson, J.: The computational complexity of abduction. Artificial Intelligence 49, 25–60 (1991)zbMATHCrossRefGoogle Scholar
  3. 3.
    Friedrich, G., Gottlob, G., Nejdl, W.: Physical impossibility instead of fault models. In: Proc. AAAI (1990)Google Scholar
  4. 4.
    Williams, B., Ragno, R.: Conflict-directed A* and its role in model-based embedded systems. Journal of Discrete Applied Mathematics (2004)Google Scholar
  5. 5.
    Vatan, F., Barrett, A., James, M., Williams, C., Mackey, R.: A novel model-based diagnosis engine: Theory and applications. In: IEEE Aerospace Conf., IEEE Computer Society Press, Los Alamitos (2003)Google Scholar
  6. 6.
    Freuder, E.C., Dechter, R., Ginsberg, B., Selman, B., Tsang, E.P.K.: Systematic versus stochastic constraint satisfaction. In: Proc. IJCAI 95, vol. 2 (1995)Google Scholar
  7. 7.
    Kask, K., Dechter, R.: Stochastic local search for Bayesian networks. In: Proc. AISTAT 1999 (1999)Google Scholar
  8. 8.
    de Kleer, J., Mackworth, A., Reiter, R.: Characterizing diagnoses and systems. Artificial Intelligence 56(8), 197–222 (1992)Google Scholar
  9. 9.
    McAllester, D.: Truth maintenance. In: Proc. AAAI 1990, vol. 2 (1990)Google Scholar
  10. 10.
    Forbus, K., de Kleer, J.: Building Problem Solvers. MIT Press, Cambridge (1993)zbMATHGoogle Scholar
  11. 11.
    Feldman, A., Provan, G., van Gemund, A.: On the performance of Safari algorithms. Technical Report TUD-SERG-2007-011, TU Delft (2007)Google Scholar
  12. 12.
    Mozetič, I.: A polynomial-time algorithm for model-based diagnosis. In: Proc. ECAI 1992, pp. 729–733 (1992)Google Scholar
  13. 13.
    Zabih, R., McAllester, D.: A rearrangement search strategy for determining propositional satisfiability. In: Proc. AAAI 1988, pp. 155–160 (1988)Google Scholar
  14. 14.
    Feldman, A., van Gemund, A.: A two-step hierarchical algorithm for model-based diagnosis. In: Proc. AAAI 2006 (July 2006)Google Scholar
  15. 15.
    Feldman, A., Provan, G., van Gemund, A.: Generating manifestations of max-fault min-cardinality diagnoses. In: Proc. DX 2007 (May 2007)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Alexander Feldman
    • 1
  • Gregory Provan
    • 2
  • Arjan van Gemund
    • 1
  1. 1.Delft University of Technology, Faculty of Electrical Engineering, Mathematics and Computer Science, Mekelweg 4, 2628 CD, DelftThe Netherlands
  2. 2.University College Cork, Department of Computer Science, College Road, CorkIreland

Personalised recommendations