Name
Abstract | ||
|---|---|---|
In this paper we propose an approach to multi-source belief revision where the trust or credibility assigned to informant agents can be revised. In our proposal, the credibility of each informant represented as a strict partial order among informant agents, will be maintained in a repository called credibility base. Upon arrival of new information concerning the credibility of its peers, an agent will be capable of revising this strict partial order, changing the trust assigned to its peers accordingly. Our goal is to formalize a set of change operators over the credibility base: expansion, contraction, prioritized, and non-prioritized revision. These operators will provide the capability of dynamically modifying the credibility of informants considering the reliability of the information. This dynamics will reflect a new perception of trust assigned to the informant, or extend the set of informants by admitting the addition of new informant agents. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1016/j.artint.2014.03.006 | Artificial Intelligence |
Keywords | Field | DocType |
Multi-agent system,Belief revision,Trust,Credibility orders,Multi-source belief revision | Data mining,Credibility,Knowledge management,Multi-agent system,Operator (computer programming),Artificial intelligence,Score,Perception,Mathematics,Belief revision,Machine learning | Journal |
Volume | Issue | ISSN |
212 | 1 | 0004-3702 |
Citations | PageRank | References |
6 | 0.49 | 21 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Luciano H. Tamargo | 1 | 31 | 6.27 |
| Alejandro Javier García | 2 | 243 | 19.98 |
| Marcelo A. Falappa | 3 | 69 | 10.22 |
| Guillermo Simari | 4 | 1819 | 128.09 |