Truth maintenance system

From Wikipedia, the free encyclopedia

Please help improve this article or section by expanding it.
Further information might be found on the talk page or at requests for expansion.
This article has been tagged since January 2007.

A truth maintenance system, or TMS, is a knowledge representation method for representing both beliefs and their dependencies. The name truth maintenance is due to the ability of these systems to restore consistency.

Many kinds of truth maintenance systems exist. Two major types are single-context and multi-context truth maintenance. In single context systems, consistency is maintained among all facts in memory (database). Multi-context systems allow consistency to be relevant to a subset of facts in memory (a context) according to the history of logical inference. This is achieved by tagging each fact or deduction with its logical history. Multi-agent truth maintenance systems perform truth maintenance across multiple memories, often located on different machines. The first multi-agent TMS was created by Mason and Johnson. It was a multi-context system. Bridgeland and Huhns created the first single-context multi-agent system.

1 Notes
2 See also
3 References
4 External links

[edit] Notes

[edit] See also

[edit] References

Bridgeland, D. M. & Huhns, M. N., Distributed Truth Maintenance. Proceedings of. AAAI–90: Eighth National Conference on Artificial Intelligence, 1990.

J. de Kleer (1986). An assumption-based TMS. Artificial Intelligence, 28:127-162.

J. Doyle. A Truth Maintenance System. AI. Vol. 12. No 3, pp. 251-272. 1979.

U. Junker and K. Konolige (1990). Computing the extensions of autoepistemic and default logics with a truth maintenance system. In Proceedings of the Eighth National Conference on Artificial Intelligence (AAAI'90), pages 278-283. The MIT Press.

Mason, C. and Johnson, R. DATMS: A Framework for Assumption Based Reasoning, in Distributed Artificial Intelligence, Vol. 2, Morgan Kaufman Publishers, Inc., 1989.

D-A. McAllster. A three valued maintenance system. Massachusetts Institute Of technology, Artificial Intelligence Laboratory. AI Memo 473. 1978.

G. M. Provan (1988). A complexity analysis of assumption-based truth maintenance systems. In B. Smith and G. Kelleher, editors, Reason Maintenance Systems and their Applications, pages 98-113. Ellis Horwood, New York.

G. M. Provan (1990). The computational complexity of multiple-context truth maintenance systems. In Proceedings of the Ninth European Conference on Artificial Intelligence (ECAI'90), pages 522-527.

R. Reiter and J. de Kleer (1987). Foundations of assumption-based truth maintenance systems: Preliminary report. In Proceedings of the Sixth National Conference on Artificial Intelligence (AAAI'87), pages 183-188. PDF