Empirical Evaluation of Similarity Coefficients for Multiagent Fault Localization

• Type: Article in International Scientific Journal
• Date: 2017

Authors

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

Journal

Title: IEEE Transactions on Systems, Man, and Cybernetics: Systems

Vol. 47

Pages: 767-782

ISSN: 2168-2216

Publisher: IEEE

Indexing

ISI Web of Knowledge - 1 Citation

Scopus - 0 Citations

Other information

Authenticus ID: P-00M-PQ7

DOI: 10.1109/tsmc.2016.2523905

Abstract (EN): Detecting and diagnosing unwanted behavior in multiagent systems (MASs) are crucial to ascertain correct operation of agents. Current techniques assume a priori knowledge to identify unexpected behavior. However, generation of MAS models is both error-prone and time-consuming, as it exponentially increases with the number of agents and their interactions. In this paper, we describe a light-weight, automatic debugging-based technique, coined extended spectrum-based fault localization for MAS (ESFL-MAS), that 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. Different heuristics may have a different impact on the diagnostic quality of ESFL- MAS. Our experimental evaluation shows that 10 out of 42 heuristics (namely accuracy, coverage, Jaccard, Laplace, least contradiction, Ochiai, Rogers and Tanimoto, simple-matching, Sorensen-dice, and support) yield the best diagnostic accuracy (96.26% on average) in the context of the MAS used in our experiments.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 16