Argumentation for interactive causal discovery
File(s)argcd.pdf (64 KB)
Published version
Author(s)
Russo, F
Type
Conference Paper
Abstract
Causal reasoning reflects how humans perceive events in the world and establish relationships among them, identifying some as causes and others as effects. Causal discovery is about agreeing on these relationships and drawing them as a causal graph. Argumentation is the way humans reason systematically about an idea: the medium we use to exchange opinions, to get to know and trust each other and possibly agree on controversial matters. Developing AI which can argue with humans about causality would allow us to understand and validate the analysis of the AI and would allow the AI to bring evidence for or against humans' prior knowledge. This is the goal of this project: to develop a novel scientific paradigm of interactive causal discovery and train AI to recognise causes and effects by debating, with humans, the results of different statistical methods.
Date Issued
2023
Date Acceptance
2023-08-19
Citation
IJCAI : proceedings of the conference / sponsored by the International Joint Conferences on Artificial Intelligence, 2023, 2023, pp.7091-7092
ISBN
9781956792034
ISSN
1045-0823
Publisher
IJCAI
Start Page
7091
End Page
7092
Journal / Book Title
IJCAI : proceedings of the conference / sponsored by the International Joint Conferences on Artificial Intelligence
Volume
2023
Copyright Statement
Copyright © 2023 International Joint Conferences on Artificial Intelligence
Identifier
https://www.ijcai.org/proceedings/2023/0820.pdf
Source
Thirty-Second International Joint Conference on Artificial Intelligence
Publication Status
Published
Start Date
2023-08-19
Finish Date
2023-08-25
Coverage Spatial
Macao, P.R. China
Date Publish Online
2023