Truth-Tracking Evaluation in Opinion-Based Argumentation

Authors

  • Juliete Rossie CRIL, CNRS, Univ. Artois, Lens, France
  • Jérôme Delobelle Université Paris Cité, LIPADE, F-75006 Paris, France
  • Sébastien Konieczny CRIL, CNRS, Univ. Artois, Lens, France
  • Srdjan Vesic CRIL, CNRS, Univ. Artois, Lens, France

DOI:

https://doi.org/10.1609/aaai.v40i23.39012

Abstract

Truth-tracking in collective reasoning systems is a core challenge in domains such as e-democracy, online deliberation, and citizen opinion polling. Our prior work introduced Opinion-Based Argumentation (OBA), a framework modeling both voting and argumentation, along with collective opinion semantics (COS) designed to select sets of arguments that are mutually coherent and aligned with agents' votes. In this paper, we first formally define the truth-tracking problem within OBA. We then introduce VAST, a comprehensive evaluation framework to systematically assess the epistemic adequacy of COS. Our empirical analysis, conducted using VAST, demonstrates substantial variation in their truth-tracking performance across diverse deliberative conditions.

Published

2026-03-14

How to Cite

Rossie, J., Delobelle, J., Konieczny, S., & Vesic, S. (2026). Truth-Tracking Evaluation in Opinion-Based Argumentation. Proceedings of the AAAI Conference on Artificial Intelligence, 40(23), 19354–19361. https://doi.org/10.1609/aaai.v40i23.39012

Issue

Section

AAAI Technical Track on Knowledge Representation and Reasoning