TY - CHAP

T1 - Square of Opposition Under Coherence

AU - Sanfilippo, Giuseppe

AU - Pfeifer, Niki

PY - 2017

Y1 - 2017

N2 - 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.

AB - 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.

UR - http://hdl.handle.net/10447/201424

UR - http://link.springer.com/chapter/10.1007/978-3-319-42972-4_50

M3 - Chapter

SN - 978-3-319-42971-7

T3 - ADVANCES IN INTELLIGENT SYSTEMS AND COMPUTING

SP - 407

EP - 414

BT - Soft Methods for Data Science

ER -