Spectrum-Based Fault Localisation for Multi-Agent Systems
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence. Main Track. Pages 1134-1139.
Abstract
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).
@inproceedings{ijcai2015p164,
title = {Spectrum-Based Fault Localisation for Multi-Agent Systems},
author = {Passos, Lúcio S. and Abreu, Rui and Rossetti, Rosaldo J. F.},
booktitle = {Proceedings of the Twenty-Fourth International Joint Conference on
Artificial Intelligence, {IJCAI-15}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Qiang Yang and Michael Wooldridge},
pages = {1134--1139},
year = {2015},
month = {7},
note = {Main Track},
url = {https://ijcai.org/proceedings/2015/164},
}
TY - CPAPER TI - Spectrum-Based Fault Localisation for Multi-Agent Systems AU - Passos, Lúcio S. AU - Abreu, Rui AU - Rossetti, Rosaldo J. F. T2 - Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-15 PB - International Joint Conferences on Artificial Intelligence PY - 2015 SP - 1134 EP - 1139 UR - https://ijcai.org/proceedings/2015/164 ER -Copied
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