On the Complexity of the Grounded Semantics for Infinite Argumentation Frameworks
- URL: http://arxiv.org/abs/2511.22376v1
- Date: Thu, 27 Nov 2025 12:13:30 GMT
- Title: On the Complexity of the Grounded Semantics for Infinite Argumentation Frameworks
- Authors: Uri Andrews, Luca San Mauro,
- Abstract summary: We use methods from mathematical logic, specifically computability and set theory, to analyze the grounded extension.<n>Finding this fixed-point requires transfinite iterations.<n>This shows a marked distinction from the finite case where the grounded extension is-time computable.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Argumentation frameworks, consisting of arguments and an attack relation representing conflicts, are fundamental for formally studying reasoning under conflicting information. We use methods from mathematical logic, specifically computability and set theory, to analyze the grounded extension, a widely-used model of maximally skeptical reasoning, defined as the least fixed-point of a natural defense operator. Without additional constraints, finding this fixed-point requires transfinite iterations. We identify the exact ordinal number corresponding to the length of this iterative process and determine the complexity of deciding grounded acceptance, showing it to be maximally complex. This shows a marked distinction from the finite case where the grounded extension is polynomial-time computable, thus simpler than other reasoning problems explored in formal argumentation.
Related papers
- Reasoning is about giving reasons [55.56111618153049]
We show that we can identify and extract the logical structure of natural language arguments in three popular reasoning datasets with high accuracies.<n>Our approach supports all forms of reasoning that depend on the logical structure of the natural language argument.
arXiv Detail & Related papers (2025-08-20T07:26:53Z) - CLATTER: Comprehensive Entailment Reasoning for Hallucination Detection [60.98964268961243]
We propose that guiding models to perform a systematic and comprehensive reasoning process allows models to execute much finer-grained and accurate entailment decisions.<n>We define a 3-step reasoning process, consisting of (i) claim decomposition, (ii) sub-claim attribution and entailment classification, and (iii) aggregated classification, showing that such guided reasoning indeed yields improved hallucination detection.
arXiv Detail & Related papers (2025-06-05T17:02:52Z) - PixelThink: Towards Efficient Chain-of-Pixel Reasoning [70.32510083790069]
PixelThink is a simple yet effective scheme that integrates externally estimated task difficulty and internally measured model uncertainty.<n>It learns to compress reasoning length in accordance with scene complexity and predictive confidence.<n> Experimental results demonstrate that the proposed approach improves both reasoning efficiency and overall segmentation performance.
arXiv Detail & Related papers (2025-05-29T17:55:49Z) - Polynomial-Time Relational Probabilistic Inference in Open Universes [14.312814866832804]
We introduce a method of first-order probabilistic inference that satisfies both the expressive power of the language used and the tractability of the computational problem posed by reasoning.<n> Specifically, we extend sum-of-squares logic of expectation to relational settings.<n>We are able to derive the tightest bounds provable by proofs of a given degree and size and establish completeness in our sum-of-squares refutations for fixed degrees.
arXiv Detail & Related papers (2025-05-07T04:14:03Z) - Critical Thinking: Which Kinds of Complexity Govern Optimal Reasoning Length? [72.70486097967124]
We formalize a framework using deterministic finite automata (DFAs)<n>We show that there exists an optimal amount of reasoning tokens such that the probability of producing a correct solution is maximized.<n>We then demonstrate an implication of these findings: being able to predict the optimal number of reasoning tokens for new problems and filtering out non-optimal length answers results in consistent accuracy improvements.
arXiv Detail & Related papers (2025-04-02T17:45:58Z) - Dialogue-based Explanations for Logical Reasoning using Structured Argumentation [0.06138671548064355]
We identify structural weaknesses of the state-of-the-art and propose a generic argumentation-based approach to address these problems.<n>Our work provides dialogue models as dialectic-proof procedures to compute and explain a query answer.<n>This allows us to construct dialectical proof trees as explanations, which are more expressive and arguably more intuitive than existing explanation formalisms.
arXiv Detail & Related papers (2025-02-16T22:26:18Z) - Advancing Algorithmic Approaches to Probabilistic Argumentation under the Constellation Approach [0.0]
We develop an algorithm for the complex task of computing the probability of a set of arguments being a complete extension.
An experimental evaluation shows promise of our approach.
arXiv Detail & Related papers (2024-07-06T12:08:38Z) - Counterfactual and Semifactual Explanations in Abstract Argumentation: Formal Foundations, Complexity and Computation [19.799266797193344]
Argumentation-based systems often lack explainability while supporting decision-making processes.
Counterfactual and semifactual explanations are interpretability techniques.
We show that counterfactual and semifactual queries can be encoded in weak-constrained Argumentation Framework.
arXiv Detail & Related papers (2024-05-07T07:27:27Z) - MetaLogic: Logical Reasoning Explanations with Fine-Grained Structure [129.8481568648651]
We propose a benchmark to investigate models' logical reasoning capabilities in complex real-life scenarios.
Based on the multi-hop chain of reasoning, the explanation form includes three main components.
We evaluate the current best models' performance on this new explanation form.
arXiv Detail & Related papers (2022-10-22T16:01:13Z) - Admissibility in Strength-based Argumentation: Complexity and Algorithms
(Extended Version with Proofs) [1.5828697880068698]
We study the adaptation of admissibility-based semantics to Strength-based Argumentation Frameworks (StrAFs)
Especially, we show that the strong admissibility defined in the literature does not satisfy a desirable property, namely Dung's fundamental lemma.
We propose a translation in pseudo-Boolean constraints for computing (strong and weak) extensions.
arXiv Detail & Related papers (2022-07-05T18:42:04Z) - A Formalisation of Abstract Argumentation in Higher-Order Logic [77.34726150561087]
We present an approach for representing abstract argumentation frameworks based on an encoding into classical higher-order logic.
This provides a uniform framework for computer-assisted assessment of abstract argumentation frameworks using interactive and automated reasoning tools.
arXiv Detail & Related papers (2021-10-18T10:45:59Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.