Publication

From user preferences to base score extraction functions in gradual argumentation

Conference Article

Conference

International Conference on Autonomous Agents and Multiagent Systems (AAMAS)

Edition

25th

Pages

2004-2012

Doc link

https://doi.org/10.65109/LIEI2830

File

Download the digital copy of the doc pdf document

Abstract

Gradual argumentation is a sub-field of Computational Argumentation from symbolic AI which is attracting attention for its ability to support transparent and contestable AI systems. It is considered a useful tool in domains such as decision-making, recommendation, debate analysis, amongst others. The outcomes in such domains are usually dependent on the arguments' base scores, which must be selected carefully. Often, this selection process requires user expertise and may not always be straightforward. On the other hand, organising the arguments by preference could simplify the task. In this work, 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), allowing the use of well-established computational tools in gradual argumentation. We outline the desirable properties of Base Score Extraction Functions, discuss some design choices, and provide an algorithm for base score extraction. Our method incorporates an approximation of non-linearities in human preferences to allow for better approximation of the real ones. Finally, we evaluate our approach both theoretically and experimentally in a robotics setting, and offer recommendations for selecting appropriate gradual semantics in practice.

Categories

common-sense reasoning, multi-agent systems.

Author keywords

Gradual Argumentation, Base Score Extraction, User Preferences

Scientific reference

A. Civit, A. Rago, A. Andriella, G. Alenyà and F. Toni. From user preferences to base score extraction functions in gradual argumentation, 25th International Conference on Autonomous Agents and Multiagent Systems, 2026, Paphos, Cyprus, pp. 2004-2012, ACM.