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 language | English |
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| Pages | 102-107 |
| Number of pages | 6 |
| State | Published - 1 Dec 2005 |
| Externally published | Yes |
| Event | 20th 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 2005 → 13 Jul 2005 |
Conference
| Conference | 20th National Conference on Artificial Intelligence and the 17th Innovative Applications of Artificial Intelligence Conference, AAAI-05/IAAI-05 |
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| Country/Territory | United States |
| City | Pittsburgh, PA |
| Period | 9/07/05 → 13/07/05 |
ASJC Scopus subject areas
- Software
- Artificial Intelligence