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ARXIV:2604.27964 · ARGUMENTATION FRAMEWORKS · SUBMITTED 01 MAY · 15:05 UTC · FRESHNESS STALE
ARXIV:2604.27964ARGUMENTATION FRAMEWORKSSUBMITTED 01 MAY · 15:05 UTCFRESHNESS STALEGiovanni Buraglio · Wolfgang Dvorak · Stefan Woltran · arXiv
Investigating splitting on the knowledge base rather than graph instantiation for computationally intractable Assumption-Based Argumentation frameworks.
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Pain Investigating splitting on the knowledge base rather than graph instantiation for computationally intractable Assumption-Based Argumentation frameworks.
Evidence 0 refs | 3 sources | 50% coverage
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Investigating splitting on the knowledge base rather than graph instantiation for computationally intractable Assumption-Based Argumentation frameworks. However, the high computational complexity of core reasoning tasks in ABA poses a significant challenge for its applicability.
Assumption-Based Argumentation (ABA) is a well-established formalism for modelling and reasoning over debates, with a wide range of applications. However, the high computational complexity of core reasoning tasks in ABA poses a significant challenge…
ScienceToStartup currently rates this 0.0/10 on the public viability pass. A paradigmatic example of this approach is splitting, where extensions of a given framework are computed incrementally, by restricting the search space to sub-frameworks…
Argumentation Frameworks moved forward this cycle; last verified May 2026. Public score 0.0/10.
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Investigating splitting on the knowledge base rather than graph instantiation for computationally intractable Assumption-Based Argumentation frameworks.
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10.48550/arXiv.2604.27964Investigating splitting on the knowledge base rather than graph instantiation for computationally intractable Assumption-Based Argumentation frameworks.
Abstract
Assumption-Based Argumentation (ABA) is a well-established formalism for modelling and reasoning over debates, with a wide range of applications. However, the high computational complexity of core reasoning tasks in ABA poses a significant challenge for its applicability. This issue is further aggravated when ABA frameworks (ABAFs) are instantiated into graph-based argumentation formalisms, such as Dung's Argumentation Frameworks (AFs) and Argumentation Frameworks with Collective Attacks (SETAFs). In knowledge representation and reasoning, a key strategy to address computational intractability is to optimise reasoning over a given knowledge base through divide-and-conquer algorithms. A paradigmatic example of this approach is splitting, where extensions of a given framework are computed incrementally, by restricting the search space to sub-frameworks only, and then combining the obtained results. This approach has been successfully applied to AFs, for which also a parametrised version has been introduced under stable semantics. However, the exponential growth produced by the instantiation might undermine the usefulness of splitting on the argument graphs induced by ABAFs. To address this issue, our work investigates the concept of splitting on the knowledge base rather than on its graph-based instantiation. Furthermore, we generalise splitting to its parametrised version for ABAFs.
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PROBLEM
Investigating splitting on the knowledge base rather than graph instantiation for computationally intractable Assumption-Based Argumentation frameworks. However, the high computational complexity of core reasoning tasks in ABA poses a significant challenge for its applicability.
METHOD
Assumption-Based Argumentation (ABA) is a well-established formalism for modelling and reasoning over debates, with a wide range of applications. However, the high computational complexity of core reasoning tasks in ABA poses a significant challenge for its applicability.
RESULT
ScienceToStartup currently rates this 0.0/10 on the public viability pass. A paradigmatic example of this approach is splitting, where extensions of a given framework are computed incrementally, by restricting the search space to sub-frameworks only, and then combining the obtai...
WHY NOW
Argumentation Frameworks moved forward this cycle; last verified May 2026. Public score 0.0/10.
{"file name": "input.pdf", "number of pages": 17, "author": "Giovanni Buraglio; Wolfgang Dvorak; Stefan Woltran", "title": "Splitting Assumption-Based Argumentation Frameworks", "creation date": null
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Investigating splitting on the knowledge base rather than graph instantiation for computationally intractable Assumption-Based Argumentation frameworks.
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Argumentation Frameworks
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