We propose a logic to reason about data collected by a number of measurement systems. The semantic of this logic is grounded on the epistemic theory of measurement that gives a central role to measurement devices and calibration. In this perspective, the lack of evidences (in the available data) for the truth or falsehood of a proposition requires the introduction of a third truth-value (the undetermined). Moreover, the data collected by a given source are here represented by means of a possible world, which provide a contextual view on the objects in the domain. We approach (possibly) conflicting data coming from different sources in a social choice theoretic fashion: we investigate viable operators to aggregate data and we represent them in our logic by means of suitable (minimal) modal operators.
CITATION STYLE
Masolo, C., & Porello, D. (2019). Towards a logic of epistemic theory of measurement. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11939 LNAI, pp. 175–188). Springer. https://doi.org/10.1007/978-3-030-34974-5_15
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