From Eigentrust to a Trust-measuring Algorithm in the Max-Plus Algebra

Juan Afanador , Nir Oren, Murilo Baptista, Maria Araujo

Research output: Chapter in Book/Report/Conference proceedingPublished conference contribution

2 Citations (Scopus)
12 Downloads (Pure)


Eigentrust is a simple and popular method for trust computation, which uses both direct and indirect information about individual performance to provide a global trust rating. This final trust value is based on eigenvectors computed through the Power Method. However, under certain network topologies, the Power Method cannot be used to identify appropriate eigenvectors. After characterising these cases, we overcome Eigentrust’s limitations by extending the algorithm’s core ideas into the Max-Plus Algebra. An empirical evaluation of our new approach demonstrates its superiority to Eigentrust.

Original languageEnglish
Title of host publicationECAI 2020
EditorsGuiseppe De Giacomo, Alejandro Catala, Bistra Dilkina, Michela Milano, Senén Barro, Alberto Bugarín, Jérôme Lang
PublisherIOS Press
Number of pages8
ISBN (Electronic)978-1-64368-101-6
ISBN (Print)978-1-64368-100-9
Publication statusPublished - 2020
Event24th European Conference on Artificial Intelligence - Santiago de Compostela, Spain
Duration: 8 Jun 202012 Jun 2020

Publication series

NameFrontiers in Artificial Intelligence and Applications
PublisherIOS Press
ISSN (Print)0922-6389
ISSN (Electronic)1879-8314


Conference24th European Conference on Artificial Intelligence
Abbreviated titleECAI 2020
CitySantiago de Compostela
Internet address


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