Spectrum-based fault localisation for multi-agent systems

• Type: Article in International Conference Proceedings Book
• Date: 2015

Authors

Passos, LS (Author) Other; Rui Abreu (Author) FEUP; Rosaldo J. F. Rossetti (Author) FEUP

Conference proceedings International

Title: IJCAI International Joint Conference on Artificial Intelligence

Pages: 1134-1140

24th International Joint Conference on Artificial Intelligence, IJCAI 2015

25 July 2015 through 31 July 2015

Indexing

Scopus - 11 Citations

Other information

Authenticus ID: P-00G-T1A

Abstract (EN): Diagnosing unwanted behaviour in Multi-Agent Systems (MASs) is crucial to ascertain agents' correct operation. However, generation of MAS models is both error-prone and time intense, as it exponentially increases with the number of agents and their interactions. In this paper, we propose a light-weight, automatic debugging-based technique, coined ESFL-MAS, which shortens the diagnostic process, while only relying on minimal information about the system. ESFL-MAS uses a heuristic that quantifies the suspiciousness of an agent to be faulty; therefore, different heuristics may have different impact on the diagnostic quality. Our experimental evaluation shows that 10 out of 42 heuristics yield the best diagnostic accuracy (96.26% on average).

Language: English

Type (Professor's evaluation): Scientific