that through a higher number of interactions, increase
in the trust of agents, increment of the agents’ number
in A, and decrease in the number of trust ratings (|T|),
the quality of estimation results enhances.
8 CONCLUSIONS
In this paper, we deﬁned tools for trust estimation in
the context of uncertainty. We addressed the uncer-
tainty, arising from the empirical data that are gen-
erated from an unknown distribution, through usage
of the possibility distributions. In addition, we ana-
lyzed the properties of merging successive possibility
distributions and introduced the Trust Event Coefﬁ-
cient for the cases where the number of agent interac-
tions should be considered. This is the ﬁrst work that
merges successive possibility distributions generated
at different levels in a multi-agent system which we
used for estimating the trust of a target agent. Fur-
thermore, we provided 2 metrics for evaluation of the
target agent’s estimated possibility distributions. We
then applied the proposed tools in intensive experi-
ments to validate our trust estimation approach.
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