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A situation-aware computational trust model for selecting partners

Title
A situation-aware computational trust model for selecting partners
Type
Article in International Scientific Journal
Year
2011
Authors
urbano, j
(Author)
Other
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oliveira, e
(Author)
FEUP
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Journal
The Journal is awaiting validation by the Administrative Services.
Vol. 225
Pages: 84-105
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Publicação em ISI Web of Knowledge ISI Web of Knowledge
Scientific classification
FOS: Natural sciences > Computer and information sciences
Other information
Authenticus ID: P-005-4CQ
Abstract (EN): Trust estimation is a fundamental process in several multi-agent systems domains, from social networks to electronic business scenarios. However, the majority of current computational trust systems is still too simplistic and is not situation-aware, jeopardizing the accuracy of the predicted trustworthiness values of agents. In this paper, we address the inclusion of context in the trust management process. We first overview recently proposed situation-aware trust models, all based on the predefinition of similarity measures between situations. Then, we present our computational trust model, and we focus on Contextual Fitness, a component of the model that adds a contextual dimensional to existing trust aggregation engines. This is a dynamic and incremental technique that extracts tendencies of behavior from the agents in evaluation and that does not imply the predefinition of similarity measures between contexts. Finally, we evaluate our trust model and compare it with other trust approaches in an agent-based, open market trading simulation scenario. The results obtained show that our dynamic and incremental technique outperforms the other approaches in open and dynamic environments. By analyzing examples derived from the experiments, we show why our technique get better results than situation-aware trust models that are based on predefined similarity measures. © 2011 Springer-Verlag Berlin Heidelberg.
Language: English
Type (Professor's evaluation): Scientific
Contact: joana.urbano@fe.up.pt; arocha@fe.up.pt; eco@fe.up.pt
No. of pages: 22
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