@conference {2595,
	title = {Spectrum-Based Fault Localisation for Multi-Agent Systems},
	booktitle = {IJCAI - 24th International Joint Conference on Artificial Intelligence},
	year = {2015},
	month = {July},
	address = {Buenos Aires},
	abstract = {<p>Diagnosing unwanted behaviour in Multi-Agent Systems (MASs) is crucial to ascertain agents{\textquoteright} 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).</p>
},
	attachments = {https://haslab.uminho.pt/sites/default/files/ruimaranhao/files/ijcai15-164.pdf},
	author = {Rui Abreu and Passos, L{\'u}cio S and Rossetti, Rosaldo JF}
}