Gradual bipolar argumentation has been shown to be an effective means for supporting decisions across a number of domains. Individual user preferences can be integrated into the domain knowledge represented by such argumentation frameworks and should be taken into account in order to provide personalised decision support. This however requires the definition of a suitable method to handle user-provided preferences in gradual bipolar argumentation, which has not been considered in previous literature. Towards filling this gap, we develop a conceptual analysis on the role of preferences in argumentation and investigate some basic principles concerning the effects they should have on the evaluation of strength in gradual argumentation semantics. We illustrate an application of our approach in the context of a review aggregation system, which has been enhanced with the ability to produce personalised outcomes based on user preferences.

Integrating User Preferences into Gradual Bipolar Argumentation for Personalised Decision Support

Baroni, Pietro
;
2024-01-01

Abstract

Gradual bipolar argumentation has been shown to be an effective means for supporting decisions across a number of domains. Individual user preferences can be integrated into the domain knowledge represented by such argumentation frameworks and should be taken into account in order to provide personalised decision support. This however requires the definition of a suitable method to handle user-provided preferences in gradual bipolar argumentation, which has not been considered in previous literature. Towards filling this gap, we develop a conceptual analysis on the role of preferences in argumentation and investigate some basic principles concerning the effects they should have on the evaluation of strength in gradual argumentation semantics. We illustrate an application of our approach in the context of a review aggregation system, which has been enhanced with the ability to produce personalised outcomes based on user preferences.
2024
Scalable Uncertainty Management - 16th International Conference, SUM 2024
MIUR (compresi PRIN FIRB,FISR)
Sébastien Destercke, Maria Vanina Martinez, Giuseppe Sanfilippo
PE6_7 Artificial intelligence, intelligent systems, multi agent systems
Esperti anonimi
Inglese
Scalable Uncertainty Management
27-29 Novembre 2024
Palermo, Italia
Internazionale
STAMPA
14
28
15
9783031762345
9783031762352
Springer
Gradual argumentation, Preferences, Decision support
   Enhancing Public Interest Communication with Argumentation
   EPICA
   MUR
   PRIN 2022
   CUP D53D23008860006
no
Not applicable
none
Battaglia, Elisa; Baroni, Pietro; Rago, Antonio; Toni, Francesca
273
info:eu-repo/semantics/conferenceObject
4
4 Contributo in Atti di Convegno (Proceeding)::4.1 Contributo in Atti di convegno
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11379/616059
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