Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1007/978-3-319-42911-3_65 | PRICAI 2016: TRENDS IN ARTIFICIAL INTELLIGENCE |
Keywords | Field | DocType |
Multi-agent system, Trust, Composite services, Capability-aware | Computer science,Computer security,Multi-agent system,Artificial intelligence,Computational trust,Hidden Markov model,Composite services,restrict,Machine learning,Distributed computing,Computation | Conference |
Volume | ISSN | Citations |
9810 | 0302-9743 | 1 |
PageRank | References | Authors |
0.35 | 8 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tung Doan Nguyen | 1 | 6 | 2.91 |
| Quan Bai | 2 | 63 | 19.77 |
| Li Weihua | 3 | 35 | 11.36 |