Towards model-based diagnosis of coordination failures

Meir Kalech, Gal A. Kaminka

Research output: Contribution to conferencePaperpeer-review

18 Scopus citations

Abstract

With increasing deployment of multi-agent and distributed systems, there is an increasing need for failure diagnosis systems. While successfully tackling key challenges in multi-agent settings, model-based diagnosis has left open the diagnosis of coordination failures, where failures often lie in the boundaries between agents, and thus the inputs to the model - with which the diagnoser simulates the system to detect discrepancies - are not known. However, it is possible to diagnose such failures using a model of the coordination between agents. This paper formalizes model-based coordination diagnosis, using two coordination primitives (concurrence and mutual exclusion). We define the consistency-based and abductive diagnosis problems within this formalization, and show that both are NP-Hard by mapping them to other known problems.

Original languageEnglish
Pages102-107
Number of pages6
StatePublished - 2005
Event20th National Conference on Artificial Intelligence and the 17th Innovative Applications of Artificial Intelligence Conference, AAAI-05/IAAI-05 - Pittsburgh, PA, United States
Duration: 9 Jul 200513 Jul 2005

Conference

Conference20th National Conference on Artificial Intelligence and the 17th Innovative Applications of Artificial Intelligence Conference, AAAI-05/IAAI-05
Country/TerritoryUnited States
CityPittsburgh, PA
Period9/07/0513/07/05

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