Title :
An adaptive recommendation trust model in multiagent system
Author :
Song, Weihua ; Phoha, Vir V. ; Xu, Xin
Author_Institution :
Coll. of Eng. & Sci., Louisiana Tech Univ., Ruston, LA, USA
Abstract :
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.
Keywords :
adaptive systems; multi-agent systems; neural nets; adaptive recommendation trust model; deceptive recommendations; estimation accuracy requirement; heterogeneous agents; multiagent system; neural network; recommendation evaluation; trust standards; Application software; Bayesian methods; Computer science; Design engineering; Educational institutions; Estimation error; Motion pictures; Multiagent systems; Neural networks; Peer to peer computing;
Conference_Titel :
Intelligent Agent Technology, 2004. (IAT 2004). Proceedings. IEEE/WIC/ACM International Conference on
Print_ISBN :
0-7695-2101-0
DOI :
10.1109/IAT.2004.1342996
