Subjective Logic Operators in Trust Assessment: an Empirical Study

TL;DR

This paper introduces geometrically interpreted subjective logic operators for trust assessment, demonstrating through empirical study that they outperform standard operators in estimating trustworthiness.

Contribution

It proposes a new geometric interpretation of SL operators and presents a family of operators that satisfy desirable properties, improving trust estimation accuracy.

Findings

Geometric operators significantly outperform standard SL operators in empirical trust estimation.

Proposed operators satisfy key desiderata for trust discounting and fusion.

New operators can be integrated into existing trust systems without modifications.

Abstract

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.