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Research PaperResearchia:202602.17025

Constrained Assumption-Based Argumentation Frameworks

Emanuele De Angelis

Abstract

Assumption-based Argumentation (ABA) is a well-established form of structured argumentation. ABA frameworks with an underlying atomic language are widely studied, but their applicability is limited by a representational restriction to ground (variable-free) arguments and attacks built from propositional atoms. In this paper, we lift this restriction and propose a novel notion of constrained ABA (CABA), whose components, as well as arguments built from them, may include constrained variables, ran...

Submitted: February 17, 2026Subjects: AI; Artificial Intelligence

Description / Details

Assumption-based Argumentation (ABA) is a well-established form of structured argumentation. ABA frameworks with an underlying atomic language are widely studied, but their applicability is limited by a representational restriction to ground (variable-free) arguments and attacks built from propositional atoms. In this paper, we lift this restriction and propose a novel notion of constrained ABA (CABA), whose components, as well as arguments built from them, may include constrained variables, ranging over possibly infinite domains. We define non-ground semantics for CABA, in terms of various notions of non-ground attacks. We show that the new semantics conservatively generalise standard ABA semantics.


Source: arXiv:2602.13135v1 - http://arxiv.org/abs/2602.13135v1 PDF: https://arxiv.org/pdf/2602.13135v1 Original Link: http://arxiv.org/abs/2602.13135v1

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Date:
Feb 17, 2026
Topic:
Artificial Intelligence
Area:
AI
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