Model-Based Diagnosis of Multi-Agent Systems: A Survey

As systems involving multiple agents are increasingly deployed, there is a growing need to diagnose failures in such systems. Model-Based Diagnosis (MBD) well-known AI technique faults In this approach, model of the diagnosed system given, and real observed. A failure announced when system's output contradicts model's expected output. The then used deduce defective components that explain unexpected observation. MBD has been being deployed distributed multi-agent survey, we summarize twenty years research field model-based diagnosis algorithms for MAS diagnosis. We depict three attributes should be considered examining diagnosis: (1) objective Either diagnosing plans or coordination faults. (2) Centralized vs. distributed. method could applied either by centralized agent manner. (3) Temporal non-temporal. MAS's temporal behaviors, whereas non-temporal conduct based on single survey diverse studies these attributes, provide novel challenges community.