An adaptive recommendation trust model in multiagent system

Weihua Song, Vir V. Phoha, Xin Xu

Research output: Chapter in Book/Entry/PoemConference contribution

18 Scopus citations

Abstract

This paper presents the design of a trust model to derive recommendation trust from heterogeneous agents. The model is a novel application of neural network in evaluating multiple recommendations of various trust standards with and without deceptions. The experimental results show that 97.22% estimation errors are less than 0.05. The results also show that the model has robust performance when there is high estimation accuracy requirement or when there are deceptive recommendations.

Original languageEnglish (US)
Title of host publicationProceedings - IEEE/WIC/ACM International Conference on Intelligent Agent Systems. IAT 2004
EditorsN. Zhong, J. Bradshaw, S.K. Pal, D. Talia, J. Liu, N. Cercone
Pages462-465
Number of pages4
StatePublished - 2004
Externally publishedYes
EventProceedings - IEEE/WIC/ACM International Conference on Intelligent Agent Technology. IAT 2004 - Beijing, China
Duration: Sep 20 2004Sep 24 2004

Publication series

NameProceedings - IEEE/WIC/ACM International Conference on Intelligent Agent Technology. IAT 2004

Other

OtherProceedings - IEEE/WIC/ACM International Conference on Intelligent Agent Technology. IAT 2004
Country/TerritoryChina
CityBeijing
Period9/20/049/24/04

ASJC Scopus subject areas

  • General Engineering

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