Abstract

Preferences and strategies are fundamental to model-based diagnosis, for specifying preferred and fall-back approaches to the diagnosis task, both to capture general and domain specific criteria, but also to tackle the complexity issue by employing heuristics. A formal framework based on extended logic programming and meta-programs is provided to represent preferences and strategies required by model-based diagnosis. This framework is clearer and more expressive than other approaches that have addressed these problems. We show how the concepts of preferences and strategies are directly programmed and captured by logic meta-programming and meta-reasoning methods, and their implementation techniques. The paper is intended as proof-of-principle that all concepts needed by a model-based diagnosis system can represented declaratively and captured by a logic meta-program. Specialized more efficient algorithms can be substituted for the simpler proof-of-principle ones we include, and are the...

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