Abstract
We investigate the application of a modal language à la Hennessy-Milner to the specific domain of evidence-based trust estimations. In particular, we refer to a context-aware notion of computational trust joining in a quantitative setting both assessment of subjective opinions and third-party recommendations. Moreover, for a comprehensive analysis of the proposed logics, we offer an axiomatization and provide soundness and completeness results.
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Notes
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An alternative approach is to employ majority logics [26]. Such logics are well suited to deal with dynamic scenarios where the number of evaluations is not fixed. The advantage of employing majority logics instead of GML is given by the fact that majority logics only specify that the (strict) majority of evaluations must be positive, without specifying a given number of those. On the contrary, in GML, this number must always be specified.
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Acknowledgements
This work was supported by a UKRI Future Leaders Fellowship, ‘Structure vs Invariants in Proofs’, project reference MR/S035540/1, and by the Italian Ministry of Education, University and Research through the PRIN 2017 project “The Manifest Image and the Scientific Image” prot. 2017ZNWW7F_004.
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Aldini, A., Curzi, G., Graziani, P., Tagliaferri, M. (2021). Trust Evidence Logic. In: Vejnarová, J., Wilson, N. (eds) Symbolic and Quantitative Approaches to Reasoning with Uncertainty. ECSQARU 2021. Lecture Notes in Computer Science(), vol 12897. Springer, Cham. https://doi.org/10.1007/978-3-030-86772-0_41
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