TY - CHAP
T1 - Probabilistic Argumentation: An Approach Based on Conditional Probability -A Preliminary Report-.
AU - Dellunde, Pilar
AU - Godo, Lluís
AU - Vidal, Amanda
N1 - DBLP License: DBLP's bibliographic metadata records provided through http://dblp.org/ are distributed under a Creative Commons CC0 1.0 Universal Public Domain Dedication. Although the bibliographic metadata records are provided consistent with CC0 1.0 Dedication, the content described by the metadata records is not. Content may be subject to copyright, rights of privacy, rights of publicity and other restrictions.
PY - 2021/5/12
Y1 - 2021/5/12
N2 - A basic form of an instantiated argument is as a pair (support, conclusion) standing for a conditional relation ‘if support then conclusion’. When this relation is not fully conclusive, a natural choice is to model the argument strength with the conditional probability of the conclusion given the support. In this paper, using a very simple language with conditionals, we explore a framework for probabilistic logic-based argumentation based on an extensive use of conditional probability, where uncertain and possibly inconsistent domain knowledge about a given scenario is represented as a set of defeasible rules quantified with conditional probabilities. We then discuss corresponding notions of attack and defeat relations between arguments, providing a basis for appropriate acceptability semantics, e.g. based on extensions or on DeLP-style dialogical trees.
AB - A basic form of an instantiated argument is as a pair (support, conclusion) standing for a conditional relation ‘if support then conclusion’. When this relation is not fully conclusive, a natural choice is to model the argument strength with the conditional probability of the conclusion given the support. In this paper, using a very simple language with conditionals, we explore a framework for probabilistic logic-based argumentation based on an extensive use of conditional probability, where uncertain and possibly inconsistent domain knowledge about a given scenario is represented as a set of defeasible rules quantified with conditional probabilities. We then discuss corresponding notions of attack and defeat relations between arguments, providing a basis for appropriate acceptability semantics, e.g. based on extensions or on DeLP-style dialogical trees.
UR - https://www.scopus.com/pages/publications/85111116827
UR - https://www.mendeley.com/catalogue/0052b2b9-9230-3035-bc49-67edee3b85d2/
U2 - 10.1007/978-3-030-75775-5_3
DO - 10.1007/978-3-030-75775-5_3
M3 - Chapter
SN - 9783030757748
SP - 25
EP - 32
BT - JELIA
ER -