posted on 2023-05-23, 14:41authored byNguyen, TD, Quan BaiQuan Bai, Li, W
Modeling trust in a real time of dynamic multi-agent systems is important but challenging, particularly when agents frequently join and leave, and the structure of the society may often change. With the increasing complexity of services, some simplified assumptions, e.g., unlimited processing capability, adopted by several trust models have shown their limitations which restrict the application of trust model in real-world situations. This paper attempts to relax the unlimited processing capability assumption of agents by introducing a capability-aware trust evaluation with temporal factor using hidden Markov model. The experimental results show that the approach not only can improve the accuracy of trust computation but also benefit the trust-aware decision making for both individual and agent group context.
History
Publication title
Proceedings of the 14th Pacific Rim International Conference on Artificial Intelligence (PRICAI 2016). Lecture Notes in Computer Science, volume 9810
Volume
9810 LNCS
Editors
R Booth and ML Zhang
Pagination
771-778
ISBN
9783319429106
Department/School
School of Information and Communication Technology
Publisher
Springer
Place of publication
Switzerland
Event title
14th Pacific Rim International Conference on Artificial Intelligence (PRICAI 2016)