Skip to main content

Temporal methods: Multi-dimensional modeling of sequential circuits

  • Published:
Annals of Mathematics and Artificial Intelligence Aims and scope Submit manuscript

Abstract

This paper discusses a mechanism for modeling the state-changing behavior of sequential devices.Temporal methods encode the temporal relationship between device variables and allow us to generalize temporal behaviors by extending Hamscher's notion of temporal abstraction. In this paper we formally define temporal methods, and describe our use of them in modeling sequential circuits. We also describe tarms, our temporal reason maintenance system which supports diagnostic reasoning about sequential circuits within the generic model-based diagnostic system (gmods).

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

References

  1. T.L. Dean and D.V. McDermott, Temporal data base management, Artificial Intelligence 32 (1987).

  2. J. de Kleer, An Assumption-based truth maintenance system, Artificial Intelligence 28 (1986).

  3. J. de Kleer, Problem solving with the atms, Artificial Intelligence 28 (1986).

  4. W.C. Hamscher, Model-based troubleshooting of digital systems, Doctoral Dissertation, MIT Artificial Intelligence Laboratory Technical Report AI-TR-1074 (August 1988).

  5. L.J. Holtzblatt, Diagnosing multiple failures using knowledge of component state,4th IEEE Conf. on Artificial Intelligence Applications, 1988.

  6. L.J. Holtzblatt, M. Neiberg and R.L. Piazza, Temporal reasoning in an assumption based reason maintenance system, Technical Report M91-22, The MITRE Corporation, Bedford, MA (1991).

    Google Scholar 

  7. C. Joubel and O. Raiman, How time changes assumptions,10th Int. Workshop on Expert Systems and their Applications, 1990.

  8. H. Kautz, The logic of persistence,Proc. 6th Natl. Conf. on Artificial Intelligence, 1986.

  9. R.A. Marcotte, L.J. Holtzblatt, R.C. Labonté and R.L. Piazza, A model-based approach for diagnosing launch system hardware,9th Int. Workshop on Expert Systems and their Applications, 1989.

  10. R.A. Marcotte, M.J. Neiberg and J.M. Schoen, System-level applications and research directions for model-based diagnostic reasoning,2nd AAAI Workshop on Model-based Reasoning, 1990.

  11. R.A. Marcotte, M.J. Neiberg, R.L. Piazza and L.J. Holtzblatt, Model-based diagnostic reasoning using VHDL, in:Performance and Fault Modeling with VHDL, ed. J.M. Schoen (Prentice-Hall, Englewood Cliffs, NJ, 1991).

    Google Scholar 

  12. Y. Shoham,Reasoning About Change (MIT Press, Cambridge, MA, 1988).

    Google Scholar 

  13. B.C. Williams, Doing time: Putting qualitative reasoning on firmer ground,Proc 6th Natl. Conf. on Artificial Intelligence, 1986.

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Holtzblatt, L.J., Neiberg, M.J., Piazza, R.L. et al. Temporal methods: Multi-dimensional modeling of sequential circuits. Ann Math Artif Intell 11, 399–413 (1994). https://doi.org/10.1007/BF01530753

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF01530753

Keywords