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pith:Q4G7JXVK

pith:2026:Q4G7JXVKMLGOWOMZSKS3EWP7HR

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From User Preferences to Base Score Extraction Functions in Gradual Argumentation (with Appendix)

Aniol Civit, Antonio Andriella, Antonio Rago, Francesca Toni, Guillem Aleny\`a

Base Score Extraction Functions convert user preferences over arguments into numerical base scores for quantitative gradual argumentation.

arxiv:2602.14674 v4 · 2026-02-16 · cs.AI

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Claims

C1strongest claim

We introduce Base Score Extraction Functions, which provide a mapping from users' preferences over arguments to base scores. These functions can be applied to the arguments of a Bipolar Argumentation Framework (BAF), supplemented with preferences, to obtain a Quantitative Bipolar Argumentation Framework (QBAF).

C2weakest assumption

That user preferences over arguments can be reliably captured by the proposed extraction functions, including their approximation of non-linearities, and that the resulting base scores produce meaningful and stable outcomes under standard gradual semantics.

C3one line summary

Base Score Extraction Functions convert user preferences into base scores for Bipolar Argumentation Frameworks, producing Quantitative Bipolar Argumentation Frameworks usable with existing gradual semantics tools, including an algorithm and robotics evaluation.

References

44 extracted · 44 resolved · 2 Pith anchors

[1] Emanuele Albini, Piyawat Lertvittayakumjorn, Antonio Rago, and Francesca Toni. 2020. Deep argumentative explanations.arXiv preprint arXiv:2012.05766 (2020) 2020

[2] Leila Amgoud. 2009. Argumentation for decision making. InArgumentation in artificial intelligence. Springer, 301–320 2009

[3] Leila Amgoud and Jonathan Ben-Naim. 2018. Evaluation of arguments in weighted bipolar graphs.International Journal of Approximate Reasoning(2018), 39–55 2018

[4] Leila Amgoud, Jonathan Ben-Naim, Dragan Doder, and Srdjan Vesic. 2016. Rank- ing arguments with compensation-based semantics. In15th International Confer- ence on Principles of Knowledge Representatio 2016

[5] Leila Amgoud and Claudette Cayrol. 1998. On the acceptability of arguments in preference-based argumentation. InProceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence. 1–7 1998

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1 paper in Pith

From User Preferences to Base Score Extraction Functions in Gradual Argumentation (with Appendix)

Receipt and verification

First computed	2026-05-17T23:38:59.937866Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

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870df4deaa62cceb399992a5b259ff3c6e7f257602fbe234790e49f7e87b22b9

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arxiv: 2602.14674 · arxiv_version: 2602.14674v4 · doi: 10.48550/arxiv.2602.14674 · pith_short_12: Q4G7JXVKMLGO · pith_short_16: Q4G7JXVKMLGOWOMZ · pith_short_8: Q4G7JXVK

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curl -sH 'Accept: application/ld+json' https://pith.science/pith/Q4G7JXVKMLGOWOMZSKS3EWP7HR \
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  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 870df4deaa62cceb399992a5b259ff3c6e7f257602fbe234790e49f7e87b22b9

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