Authors: Federico Cerutti,Alice Toniolo,Nir Oren,Timothy J. Norman
ArXiv: 1312.4828
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Abstract URL: http://arxiv.org/abs/1312.4828v1
Computational trust mechanisms aim to produce trust ratings from both direct
and indirect information about agents' behaviour. Subjective Logic (SL) has
been widely adopted as the core of such systems via its fusion and discount
operators. In recent research we revisited the semantics of these operators to
explore an alternative, geometric interpretation. In this paper we present a
principled desiderata for discounting and fusion operators in SL. Building upon
this we present operators that satisfy these desirable properties, including a
family of discount operators. We then show, through a rigorous empirical study,
that specific, geometrically interpreted operators significantly outperform
standard SL operators in estimating ground truth. These novel operators offer
real advantages for computational models of trust and reputation, in which they
may be employed without modifying other aspects of an existing system.