ABA learning via ASP
File(s)
Published version
Author(s)
De Angelis, Emanuele
Proietti, Maurizio
Toni, Francesca
Type
Conference Paper
Abstract
Recently, ABA Learning has been proposed as a form of symbolic machine learning for drawing Assumption-Based Argumentation frameworks from background knowledge and positive and negative examples. We propose a novel method for implementing ABA Learning using Answer Set
Programming as a way to help guide Rote Learning and generalisation in ABA Learning.
Programming as a way to help guide Rote Learning and generalisation in ABA Learning.
Date Issued
2023-07-09
Date Acceptance
2023-05-24
Citation
Electronic Proceedings in Theoretical Computer Science, 2023, 385, pp.1-8
ISSN
2075-2180
Publisher
Open Publishing Association
Start Page
1
End Page
8
Journal / Book Title
Electronic Proceedings in Theoretical Computer Science
Volume
385
Copyright Statement
© De Angelis, Proietti, Toni This work is licensed under the
Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/)
Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/)
License URL
Source
ICLP 2023
Publication Status
Published
Start Date
2023-07-09
Finish Date
2023-07-15
Coverage Spatial
London, UK