Model-Based Diagnosis often cannot be directly exploited for embedded software, which must run with very strict constraints on memory and time. It is however possible to compile the knowledge explicited by a model-based diagnostic engine into a decision tree that serves as the basis for on-board diagnostic software. In order to exploit temporal information possibly present in the model, temporal decision trees for diagnosis have been introduced. This paper presents an extension to the temporal decision trees framework that widens its applicability.

Temporal Decision Trees for Diagnosis:An Extension

PICARDI, Claudia
2003-01-01

Abstract

Model-Based Diagnosis often cannot be directly exploited for embedded software, which must run with very strict constraints on memory and time. It is however possible to compile the knowledge explicited by a model-based diagnostic engine into a decision tree that serves as the basis for on-board diagnostic software. In order to exploit temporal information possibly present in the model, temporal decision trees for diagnosis have been introduced. This paper presents an extension to the temporal decision trees framework that widens its applicability.
2003
Eight Conference of the Italian Association for Artificial Intelligence (AI*IA)
Pisa, Italy
23-26 settembre 2003
2829
14
26
C. PICARDI
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/7899
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