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. © 2004 IEEE.
CITATION STYLE
Song, W., Phoha, V. V., & Xu, X. (2004). An adaptive recommendation trust model in multiagent system. In Proceedings - IEEE/WIC/ACM International Conference on Intelligent Agent Technology. IAT 2004 (pp. 462–465). https://doi.org/10.1109/iat.2004.1342996
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