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Autores principales: Kampik, Timotheus, Potyka, Nico, Yin, Xiang, Čyras, Kristijonas, Toni, Francesca
Formato: Preprint
Publicado: 2024
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Acceso en línea:https://arxiv.org/abs/2401.08879
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author Kampik, Timotheus
Potyka, Nico
Yin, Xiang
Čyras, Kristijonas
Toni, Francesca
author_facet Kampik, Timotheus
Potyka, Nico
Yin, Xiang
Čyras, Kristijonas
Toni, Francesca
contents We present a principle-based analysis of contribution functions for quantitative bipolar argumentation graphs that quantify the contribution of one argument to another. The introduced principles formalise the intuitions underlying different contribution functions as well as expectations one would have regarding the behaviour of contribution functions in general. As none of the covered contribution functions satisfies all principles, our analysis can serve as a tool that enables the selection of the most suitable function based on the requirements of a given use case.
format Preprint
id arxiv_https___arxiv_org_abs_2401_08879
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Contribution Functions for Quantitative Bipolar Argumentation Graphs: A Principle-based Analysis
Kampik, Timotheus
Potyka, Nico
Yin, Xiang
Čyras, Kristijonas
Toni, Francesca
Artificial Intelligence
We present a principle-based analysis of contribution functions for quantitative bipolar argumentation graphs that quantify the contribution of one argument to another. The introduced principles formalise the intuitions underlying different contribution functions as well as expectations one would have regarding the behaviour of contribution functions in general. As none of the covered contribution functions satisfies all principles, our analysis can serve as a tool that enables the selection of the most suitable function based on the requirements of a given use case.
title Contribution Functions for Quantitative Bipolar Argumentation Graphs: A Principle-based Analysis
topic Artificial Intelligence
url https://arxiv.org/abs/2401.08879