Name
Abstract | ||
|---|---|---|
Trust and personalization are two important notions in social network that have been intensively developed in multi-agent systems during the last years. But there is few works about integrating these notions in the same network of agents. In this paper, we present a way to integrate trust and personalization in an agent network by adding a new dimension to the calculus of trust in the model of Falcone and Castelfranchi, which we will call a similarity degree. We first present the fundamental notions and models we use, then the model of integration we developed and finally the experiments we made to validate our model. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/978-3-642-11819-7_19 | AGENTS AND ARTIFICIAL INTELLIGENCE |
Keywords | Field | DocType |
Trust,Agent network,Personalization,Social network | Social network,Computer science,Human–computer interaction,Artificial intelligence,Machine learning,Personalization | Conference |
Volume | ISSN | Citations |
67 | 1865-0929 | 1 |
PageRank | References | Authors |
0.38 | 7 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Laurent Lacomme | 1 | 6 | 1.86 |
| Yves Demazeau | 2 | 684 | 138.78 |
| Valérie Camps | 3 | 90 | 17.42 |