Towards a Better Understanding of Context and Context-Awareness
HUC '99 Proceedings of the 1st international symposium on Handheld and Ubiquitous Computing
An integrated trust and reputation model for open multi-agent systems
Autonomous Agents and Multi-Agent Systems
Journal of the American Society for Information Science and Technology
Formal Analysis of Trust Dynamics in Human and Software Agent Experiments
CIA '07 Proceedings of the 11th international workshop on Cooperative Information Agents XI
Computing Confidence Values: Does Trust Dynamics Matter?
EPIA '09 Proceedings of the 14th Portuguese Conference on Artificial Intelligence: Progress in Artificial Intelligence
Trust Theory: A Socio-Cognitive and Computational Model
Trust Theory: A Socio-Cognitive and Computational Model
Facing openness with socio-cognitive trust and categories
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume One
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Trust is a construct of paramount importance in society. Accordingly, computational trust is evolving fast in order to allow trust in artificial societies. Despite the advances in this research field, most computational trust approaches evaluate trust by estimating the trustworthiness of the agents under evaluation (the trustees), without however distinguishing between the different dimensions of trustworthiness, such as ability and benevolence. In this paper, we propose different techniques to extract the ability of the trustee in the task at hand and to infer the benevolence of the trustee toward the truster when the trust judgment is made. Moreover, we propose to dynamically change the relative importance and impact of both ability and benevolence on the perceived trustworthiness of the trustee, taking into consideration the development of the relationship between the truster and the trustee and the disposition of the truster in the specific situation. Finally, we set an experimental scenario to evaluate our approach. The results obtained from these experiments show that the proposed techniques significantly improve the reliability of the estimation of the trustworthiness of agents.