On Strong and Weak Admissibility in Non-Flat Assumption-Based Argumentation
- URL: http://arxiv.org/abs/2508.11182v1
- Date: Fri, 15 Aug 2025 03:13:07 GMT
- Title: On Strong and Weak Admissibility in Non-Flat Assumption-Based Argumentation
- Authors: Matti Berthold, Lydia Blümel, Anna Rapberger,
- Abstract summary: We study two prominent alternatives to the standard notion of admissibility from abstract argumentation.<n>We introduce the respective preferred, complete and grounded semantics for general (sometimes called non-flat) ABA.<n>We show that the central modularization property is maintained under classical, strong, and weak admissibility.
- Score: 4.583931917131698
- License: http://creativecommons.org/licenses/by-sa/4.0/
- Abstract: In this work, we broaden the investigation of admissibility notions in the context of assumption-based argumentation (ABA). More specifically, we study two prominent alternatives to the standard notion of admissibility from abstract argumentation, namely strong and weak admissibility, and introduce the respective preferred, complete and grounded semantics for general (sometimes called non-flat) ABA. To do so, we use abstract bipolar set-based argumentation frameworks (BSAFs) as formal playground since they concisely capture the relations between assumptions and are expressive enough to represent general non-flat ABA frameworks, as recently shown. While weak admissibility has been recently investigated for a restricted fragment of ABA in which assumptions cannot be derived (flat ABA), strong admissibility has not been investigated for ABA so far. We introduce strong admissibility for ABA and investigate desirable properties. We furthermore extend the recent investigations of weak admissibility in the flat ABA fragment to the non-flat case. We show that the central modularization property is maintained under classical, strong, and weak admissibility. We also show that strong and weakly admissible semantics in non-flat ABA share some of the shortcomings of standard admissible semantics and discuss ways to address these.
Related papers
- Revisiting Follow-the-Perturbed-Leader with Unbounded Perturbations in Bandit Problems [60.58442311545223]
Follow-the-Regularized-Leader (FTRL) policies have achieved Best-of-Both-Worlds (BOBW) results in various settings through hybrid regularizers.<n>We revisit classical FTRL-FTPL duality for unbounded perturbations and establish BOBW results for FTPL under a broad family of asymmetric Fr'echet-type perturbations.
arXiv Detail & Related papers (2025-08-26T02:12:18Z) - On Gradual Semantics for Assumption-Based Argumentation [15.021229450879316]
In computational argumentation, gradual semantics are fine-grained alternatives to extension-based and labelling-based semantics.<n>We show that our gradual ABA semantics satisfy suitable adaptations of desirable properties, such as balance and monotonicity.
arXiv Detail & Related papers (2025-07-14T09:02:45Z) - A Survey on Latent Reasoning [100.54120559169735]
Large Language Models (LLMs) have demonstrated impressive reasoning capabilities.<n>CoT reasoning that verbalizes intermediate steps limits the model's expressive bandwidth.<n>Latent reasoning tackles this bottleneck by performing multi-step inference entirely in the model's continuous hidden state.
arXiv Detail & Related papers (2025-07-08T17:29:07Z) - The Curse of CoT: On the Limitations of Chain-of-Thought in In-Context Learning [56.574829311863446]
Chain-of-Thought (CoT) prompting has been widely recognized for its ability to enhance reasoning capabilities in large language models (LLMs)<n>We demonstrate that CoT and its reasoning variants consistently underperform direct answering across varying model scales and benchmark complexities.<n>Our analysis uncovers a fundamental hybrid mechanism of explicit-implicit reasoning driving CoT's performance in pattern-based ICL.
arXiv Detail & Related papers (2025-04-07T13:51:06Z) - A Law Reasoning Benchmark for LLM with Tree-Organized Structures including Factum Probandum, Evidence and Experiences [76.73731245899454]
We propose a transparent law reasoning schema enriched with hierarchical factum probandum, evidence, and implicit experience.<n>Inspired by this schema, we introduce the challenging task, which takes a textual case description and outputs a hierarchical structure justifying the final decision.<n>This benchmark paves the way for transparent and accountable AI-assisted law reasoning in the Intelligent Court''
arXiv Detail & Related papers (2025-03-02T10:26:54Z) - Rethinking State Disentanglement in Causal Reinforcement Learning [78.12976579620165]
Causality provides rigorous theoretical support for ensuring that the underlying states can be uniquely recovered through identifiability.
We revisit this research line and find that incorporating RL-specific context can reduce unnecessary assumptions in previous identifiability analyses for latent states.
We propose a novel approach for general partially observable Markov Decision Processes (POMDPs) by replacing the complicated structural constraints in previous methods with two simple constraints for transition and reward preservation.
arXiv Detail & Related papers (2024-08-24T06:49:13Z) - On the Correspondence of Non-flat Assumption-based Argumentation and Logic Programming with Negation as Failure in the Head [20.981256612743145]
We show a correspondence between non-flat ABA and LPs with negation as failure in their head.
We then extend this result to so-called set-stable ABA semantics, originally defined for the fragment of non-flat ABA called bipolar ABA.
We showcase how to define set-stable semantics for LPs with negation as failure in their head and show the correspondence to set-stable ABA semantics.
arXiv Detail & Related papers (2024-05-15T15:10:03Z) - Instantiations and Computational Aspects of Non-Flat Assumption-based Argumentation [18.32141673219938]
We study an instantiation-based approach for reasoning in possibly non-flat ABA.
We propose two algorithmic approaches for reasoning in possibly non-flat ABA.
arXiv Detail & Related papers (2024-04-17T14:36:47Z) - Non-flat ABA is an Instance of Bipolar Argumentation [23.655909692988637]
Assumption-based Argumentation (ABA) is a well-known structured argumentation formalism.
A common restriction imposed on ABA frameworks (ABAFs) is that they are flat.
No translation exists from general, possibly non-flat ABAFs into any kind of abstract argumentation formalism.
arXiv Detail & Related papers (2023-05-21T13:18:08Z) - Provable Unrestricted Adversarial Training without Compromise with Generalizability [44.02361569894942]
Adversarial training (AT) is widely considered as the most promising strategy to defend against adversarial attacks.
The existing AT methods often achieve adversarial robustness at the expense of standard generalizability.
We propose a novel AT approach called Provable Unrestricted Adversarial Training (PUAT)
arXiv Detail & Related papers (2023-01-22T07:45:51Z) - 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) - On Lower Bounds for Standard and Robust Gaussian Process Bandit
Optimization [55.937424268654645]
We consider algorithm-independent lower bounds for the problem of black-box optimization of functions having a bounded norm.
We provide a novel proof technique for deriving lower bounds on the regret, with benefits including simplicity, versatility, and an improved dependence on the error probability.
arXiv Detail & Related papers (2020-08-20T03:48:14Z)
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.