Under Uncertainty Trust Estimation through Unknown Agents, in a Multi-valued Trust Environment

In a world where an increasing number of transactions are made on the web, there is a need for a trust evaluation tool dealing with uncertainty, e.g., for customers interested in evaluating the trustworthiness of an unknown service provider throughout queries to other customers of unknown reliability. In this paper, we propose to estimate the trust of an unknown agent, say a^D, through the information given by a group of agents who have interacted with agent a^D. This group of agents is assumed to have an unknown reliability. In order to tackle the uncertainty associated with the trust of unknown agents, we suggest to use possibility distributions. We introduce a new certainty metric to measure the degree of agreement of the information reported by the group of agents about agent a^D. Fusion rules are then used to estimate the possibility distribution of agent a^D´s trust. To the best of our knowledge, this is the first paper that estimates trust, out of empirical data, subject to some uncertainty, in a discrete multi-valued trust environment. Numerical experiments are presented to validate the proposed tools.