多智能体系统中的自适应推荐信任模型

Proceedings. IEEE/WIC/ACM International Conference on Intelligent Agent Technology, 2004. (IAT 2004). Pub Date : 2004-09-20 DOI:10.1109/IAT.2004.1342996

Weihua Song, V. Phoha, Xin Xu

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引用次数: 26

摘要

本文提出了一个信任模型的设计，以从异构代理中获得推荐信任。该模型是神经网络在评估有欺骗和无欺骗的各种信任标准的多重推荐中的一种新应用。实验结果表明，97.22%的估计误差小于0.05。结果还表明，该模型在估计精度要求较高或存在欺骗性推荐的情况下具有良好的鲁棒性。

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An adaptive recommendation trust model in multiagent system

This work 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.

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来源期刊

Proceedings. IEEE/WIC/ACM International Conference on Intelligent Agent Technology, 2004. (IAT 2004).

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