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New expressivity results for uncertain argumentation frameworks published

By PulseAugur Editorial · [1 sources] ·

Researchers have developed new expressivity results for structured argumentation frameworks that incorporate uncertain rules and premises. The study introduces a novel notion of comparative expressivity, allowing for the comparison of different formalisms in their ability to generate abstract argumentation frameworks. The findings include both positive and negative results when comparing abstract models with structured models like ASPIC+, Assumption-Based Argumentation, and Deductive Argumentation. AI

IMPACT This research contributes to the theoretical foundations of AI systems that need to reason under uncertainty, potentially improving their robustness and reliability.

RANK_REASON The cluster contains an academic paper published on arXiv detailing theoretical results in formal argumentation. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New expressivity results for uncertain argumentation frameworks published

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The cluster contains an academic paper published on arXiv detailing theoretical results in formal argumentation. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Carlo Proietti, Antonio Yuste-Ginel ·

    Expressivity Results for Structured Argumentation Frameworks with Uncertain Rules and Premises

    arXiv:2510.18631v3 Announce Type: replace Abstract: Modelling qualitative uncertainty in formal argumentation is essential both for practical applications and theoretical understanding. Yet, most existing work focuses on abstract models of argumentation under uncertainty. Followi…

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