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Juliete Rossie

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2 papers

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AAAI Conference 2026 Conference Paper

Truth-Tracking Evaluation in Opinion-Based Argumentation

Juliete Rossie
Jérôme Delobelle
Sébastien Konieczny
Srdjan Vesic

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.

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KR Conference 2024 Conference Paper

Collective Satisfaction Semantics for Opinion Based Argumentation

Juliete Rossie
Jérôme Delobelle
Sébastien Konieczny
Clément Lens
Srdjan Vesic

Voting on arguments in a debate is a natural approach for reaching a consensual decision. Despite this, there are few formal methods of abstract argumentation dealing with the use of votes in the process of selecting accepted arguments. We introduce the Opinion Based Argumentation (OBA) framework, where individuals can vote (or abstain) for or against arguments in a Dung argumentation framework. Our research aims to determine the most appropriate collective decisions within this framework. We propose a new semantics for this framework, called Collective Satisfaction Semantics (CSS), to evaluate the acceptability of arguments and study their properties. Additionally, we compare these semantics against alternative methods adapted from related literature to provide insights into their relative effectiveness.

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