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is the first work that merges successive possibility distributions generated at different
levels of a multi-agent system. We used this approach in order to estimate the trust of an
unknown agent, through the information provided by a set of self-interested agents who
are partially known to the explorer agent. The approach presented in this paper can be
extended to estimate the trust of an agent of interest in the multi-agent systems, who can
be reached through a set of sequentially connected agents. In addition, we addressed un-
certainty in our trust model, arising from variability and ignorance in the empirical data
that are generated from an unknown distribution, through usage of the possibility dis-
tributions. Finally, we applied the proposed merging approach in extensive experiments
to validate our estimation results.
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