Forging argumentative explanations from causal models
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Published version
Author(s)
Rago, A
Russo, F
Albini, E
Baroni, P
Toni, F
Type
Conference Paper
Abstract
We introduce a conceptualisation for generating argumentation frameworks (AFs) from causal models for the purpose of forging explanations for models' outputs. The conceptualisation is based on reinterpreting properties of semantics of AFs as explanation moulds, which are means for characterising argumentative relations. We demonstrate our methodology by reinterpreting the property of bi-variate reinforcement in bipolar AFs, showing how the extracted bipolar AFs may be used as relation-based explanations for the outputs of causal models.
Date Issued
2022-02-14
Date Acceptance
2022-02-01
Citation
CEUR Workshop Proceedings, 2022, 3086, pp.1-15
ISSN
1613-0073
Publisher
CEUR Workshop Proceedings
Start Page
1
End Page
15
Journal / Book Title
CEUR Workshop Proceedings
Volume
3086
Copyright Statement
© 2021 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution
4.0 International (CC BY 4.0).
4.0 International (CC BY 4.0).
License URL
Identifier
https://ceur-ws.org/Vol-3086/paper3.pdf
Source
Proceedings of the 5th Workshop on Advances in Argumentation in Artificial Intelligence 2021 co-located with the 20th International Conference of the Italian Association for Artificial Intelligence (AIxIA 2021)
Publication Status
Published
Start Date
2021-11-29
Coverage Spatial
Milan, Italy
Date Publish Online
2022-02-14