2013/11/19 by Federico Cerutti, Alice Toniolo, Cerutti, Federico +5
Computer Science · Social Sciences · #Access Control and Trust #Artificial Intelligence (cs.AI) #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Logic in Computer Science (cs.LO) #Logic, Reasoning, and Knowledge #cs.AI #cs.CR #cs.LO
paper · pdf · doi:10.48550/arxiv.1312.4828
Submitted to Information Systems Frontiers Journal
arxiv created 2013/11/19 · openalex publication_date 2013/11/19 · arxiv updated 2013/12/18 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.