Trust and reputation are fundamental concepts in multi-agent systems, but at the same time are significant to human life. The purpose of this paper is to find a way to enhance collective intelligence within organizations. First, we present some perspectives concerning the concepts of collective intelligence, trust and reputation. Then we suggest four computational models of trust and reputation, describing the main characteristics of each model and based on a cognitive model of trust, it is shown up how trust can increase collective intelligence in an organization. We try to simulate agents' behavior using the preferential attachment hypothesis. © 2009 Springer Berlin Heidelberg.
CITATION STYLE
Scarlat, E., & Maries, I. (2009). Towards an increase of collective intelligence within organizations using trust and reputation models. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5796 LNAI, pp. 140–151). Springer Verlag. https://doi.org/10.1007/978-3-642-04441-0_12
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