Diagnostic reasoning based on structure and behavior
Artificial Intelligence - Special volume on qualitative reasoning about physical systems
A theory of diagnosis from first principles
Artificial Intelligence
Artificial Intelligence
Information Processing Letters
Using crude probability estimates to guide diagnosis
Artificial Intelligence
"Physical negation": integrating fault models into the general diagnostic engine
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 2
Diagnosis with behavioral modes
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 2
Detecting and locating faults in the control software of autonomous mobile robots
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
No faults in structure?: how to diagnose hidden interactions
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Using AI techniques for fault localization in component-oriented software systems
MICAI'06 Proceedings of the 5th Mexican international conference on Artificial Intelligence
Dependent Failures in Consistency-based Diagnosis
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
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Previous works have proposed to apply model-based diagnosis (MBD) techniques to detect and locate faults in the control software of mobile autonomous robots at runtime. The localization of faults at the level of software components enables the autonomous repair of the system by restarting failed components. Unfortunately, classical MBD approaches assume that components fail independently. In this paper we show that dependent failures are very common in this application domain and we propose the concept of diagnosis environments (DEs) in order to tackle the arising problems. We provide an algorithm for the computation of DEs and present the results of case studies.