From fine-grained properties to broad principles for gradual argumentation: A principled spectrum
File(s)props_ijar.pdf (1001.24 KB)
Accepted version
Author(s)
Baroni, Pietro
Rago, Antonio
Toni, Francesca
Type
Journal Article
Abstract
The study of properties of gradual evaluation methods in argumentation has received increasing attention in recent years, with studies devoted to various classes of frameworks/ methods leading to conceptually similar but formally distinct properties in different contexts. In this paper we provide a novel systematic analysis for this research landscape by making three main contributions. First, we identify groups of conceptually related properties in the literature, which can be regarded as based on common patterns and, using these patterns, we evidence that many further novel properties can be considered. Then, we provide a simplifying and unifying perspective for these groups of properties by showing that they are all implied by novel parametric principles of (either strict or non-strict) balance and monotonicity. Finally, we show that (instances of) these principles (and thus the group, literature and novel properties that they imply) are satisfied by several quantitative argumentation formalisms in the literature, thus confirming the principles' general validity and utility to support a compact, yet comprehensive, analysis of properties of gradual argumentation.
Date Issued
2019-02-01
Date Acceptance
2018-11-28
Citation
International Journal of Approximate Reasoning, 2019, 105 (1), pp.252-286
ISSN
0888-613X
Publisher
Elsevier
Start Page
252
End Page
286
Journal / Book Title
International Journal of Approximate Reasoning
Volume
105
Issue
1
Copyright Statement
© 2018 Elsevier Inc. All rights reserved. This manuscript is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence http://creativecommons.org/licenses/by-nc-nd/4.0/
Sponsor
Engineering & Physical Science Research Council (EPSRC)
Grant Number
EP/P029558/1
Subjects
Science & Technology
Technology
Computer Science, Artificial Intelligence
Computer Science
Bipolar argumentation
Quantitative argumentation
STRENGTH
Artificial Intelligence & Image Processing
0103 Numerical and Computational Mathematics
0104 Statistics
0801 Artificial Intelligence and Image Processing
Publication Status
Published
Date Publish Online
2018-12-03