Various semantics for studying the square of opposition have been proposed recently. So far, only (Gilio et al., 2016) studied a probabilistic version of the square where the sentences were interpreted by (negated) defaults. We extend this work by interpreting sentences by imprecise (set-valued) probability assessments on a sequence of conditional events. We introduce the acceptability of a sentence within coherence-based probability theory. We analyze the relations of the square in terms of acceptability and show how to construct probabilistic versions of the square of opposition by forming suitable tripartitions. Finally, as an application, we present a new square involving generalized quantifiers.
|Titolo della pubblicazione ospite||Soft Methods for Data Science|
|Numero di pagine||8|
|Stato di pubblicazione||Published - 2017|
|Nome||ADVANCES IN INTELLIGENT SYSTEMS AND COMPUTING|