IJCAI 2022poster5 citations

In Data We Trust: The Logic of Trust-Based Beliefs

Junli Jiang, Pavel Naumov

Abstract

The paper proposes a data-centred approach to reasoning about the interplay between trust and beliefs. At its core, is the modality "under the assumption that one dataset is trustworthy, another dataset informs a belief in a statement". The main technical result is a sound and complete logical system capturing the properties of this modality.

Knowledge Representation and Reasoning: Reasoning about Knowledge and Belief
BibTeX
@inproceedings{ijcai2022p372,
  title     = {In Data We Trust: The Logic of Trust-Based Beliefs},
  author    = {Jiang, Junli and Naumov, Pavel},
  booktitle = {Proceedings of the Thirty-First International Joint Conference on
               Artificial Intelligence, {IJCAI-22}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
  editor    = {Lud De Raedt},
  pages     = {2683--2689},
  year      = {2022},
  month     = {7},
  note      = {Main Track},
  doi       = {10.24963/ijcai.2022/372},
  url       = {https://doi.org/10.24963/ijcai.2022/372},
}
In Data We Trust: The Logic of Trust-Based Beliefs · IJCAI 2022