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[full paper] |
Martin Sachenbacher, Brian Williams
Constraint optimization is at the core of many problems in Artificial Intelligence. In this paper, we frame model-based diagnosis as a constraint optimization problem over lattices. We then show how it can be captured in a framework for "soft" constraints known as semiring-CSPs. The well-defined mathematical properties of a semiring-CSP allow to devise efficient solution methods that are based on decomposing diagnostic problems into trees and applying dynamic programming. We relate the approach to SAB and TREE*, two diagnosis algorithms for tree-structured systems, which correspond to special cases of semiring-based constraint optimization.
Keywords: Diagnosis, Model-Based Reasoning, Constraint Programming
Citation: Martin Sachenbacher, Brian Williams: Diagnosis as Semiring-based Constraint Optimization . In R.López de Mántaras and L.Saitta (eds.): ECAI2004, Proceedings of the 16th European Conference on Artificial Intelligence, IOS Press, Amsterdam, 2004, pp.873-877.