On resolving conflicts between arguments

• URL: http://arxiv.org/abs/2209.09838v1
• Date: Tue, 20 Sep 2022 16:31:19 GMT
• Title: On resolving conflicts between arguments
• Authors: Nico Roos
• Abstract summary: In legal argumentation, meta-rules determine the valid arguments by considering the last defeasible rule of each argument involved in a conflict. We propose a new argument system where, instead of deriving a defeat relation between arguments, emphundercutting-arguments for the defeat of defeasible rules are constructed.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Argument systems are based on the idea that one can construct arguments for propositions; i.e., structured reasons justifying the belief in a proposition. Using defeasible rules, arguments need not be valid in all circumstances, therefore, it might be possible to construct an argument for a proposition as well as its negation. When arguments support conflicting propositions, one of the arguments must be defeated, which raises the question of \emph{which (sub-)arguments can be subject to defeat}? In legal argumentation, meta-rules determine the valid arguments by considering the last defeasible rule of each argument involved in a conflict. Since it is easier to evaluate arguments using their last rules, \emph{can a conflict be resolved by considering only the last defeasible rules of the arguments involved}? We propose a new argument system where, instead of deriving a defeat relation between arguments, \emph{undercutting-arguments} for the defeat of defeasible rules are constructed. This system allows us, (\textit{i}) to resolve conflicts (a generalization of rebutting arguments) using only the last rules of the arguments for inconsistencies, (\textit{ii}) to determine a set of valid (undefeated) arguments in linear time using an algorithm based on a JTMS, (\textit{iii}) to establish a relation with Default Logic, and (\textit{iv}) to prove closure properties such as \emph{cumulativity}. We also propose an extension of the argument system that enables \emph{reasoning by cases}.

Related papers

• Understanding Enthymemes in Argument Maps: Bridging Argument Mining and Logic-based Argumentation [11.633929083694388]
  In this paper, we assume that an argument map contains the premises and claims of arguments, and support and attack relationships between them. To understand and to automatically analyse that argument map, it would be desirable to instantiate that argument map with logical arguments. We address this need by using classical logic for representing the explicit information in the text, and using default logic for representing the implicit information in the text.
  arXiv  Detail & Related papers  (2024-08-16T10:30:30Z)
• CASA: Causality-driven Argument Sufficiency Assessment [79.13496878681309]
  We propose CASA, a zero-shot causality-driven argument sufficiency assessment framework. PS measures how likely introducing the premise event would lead to the conclusion when both the premise and conclusion events are absent. Experiments on two logical fallacy detection datasets demonstrate that CASA accurately identifies insufficient arguments.
  arXiv  Detail & Related papers  (2024-01-10T16:21:18Z)
• A Unifying Framework for Learning Argumentation Semantics [50.69905074548764]
  We present a novel framework, which uses an Inductive Logic Programming approach to learn the acceptability semantics for several abstract and structured argumentation frameworks in an interpretable way. Our framework outperforms existing argumentation solvers, thus opening up new future research directions in the area of formal argumentation and human-machine dialogues.
  arXiv  Detail & Related papers  (2023-10-18T20:18:05Z)
• Semi-Abstract Value-Based Argumentation Framework [0.0]
  Phan Minh Dung proposed abstract argumentation framework, which models argumentation using directed graphs where structureless arguments are the nodes and attacks among the arguments are the edges. This thesis showcases two such extensions -- value-based argumentation framework by Trevor Bench-Capon (2002) and semi-abstract argumentation framework by Esther Anna Corsi and Christian Ferm" The contribution of this thesis is two-fold. Firstly, the new semi-abstract value-based argumentation framework is introduced. This framework maps propositional formulae associated with individual arguments to a set of ordered values.
  arXiv  Detail & Related papers  (2023-09-25T13:10:56Z)
• ArgU: A Controllable Factual Argument Generator [0.0]
  ArgU is a neural argument generator capable of producing factual arguments from input facts and real-world concepts. We have compiled and released an annotated corpora of 69,428 arguments spanning six topics and six argument schemes.
  arXiv  Detail & Related papers  (2023-05-09T10:49:45Z)
• Towards Full-Fledged Argument Search: A Framework for Extracting and Clustering Arguments from Unstructured Text [0.0]
  Argument search aims at identifying arguments in natural language texts. Existing frameworks address only specific components of argument search. We propose a framework for addressing these shortcomings.
  arXiv  Detail & Related papers  (2021-11-30T23:05:05Z)
• 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)
• Intrinsic Argument Strength in Structured Argumentation: a Principled Approach [0.0]
  We study methods for assigning an argument its intrinsic strength, based on the strengths of the premises and inference rules used to form said argument. We first define a set of principles, which are properties that strength assigning methods might satisfy. We then propose two such methods and analyse which principles they satisfy.
  arXiv  Detail & Related papers  (2021-09-01T11:54:15Z)
• Reinforcement Learning-based Dialogue Guided Event Extraction to Exploit Argument Relations [70.35379323231241]
  This paper presents a better approach for event extraction by explicitly utilizing the relationships of event arguments. We employ reinforcement learning and incremental learning to extract multiple arguments via a multi-turned, iterative process. Experimental results show that our approach consistently outperforms seven state-of-the-art event extraction methods.
  arXiv  Detail & Related papers  (2021-06-23T13:24:39Z)
• Exploring Discourse Structures for Argument Impact Classification [48.909640432326654]
  This paper empirically shows that the discourse relations between two arguments along the context path are essential factors for identifying the persuasive power of an argument. We propose DisCOC to inject and fuse the sentence-level structural information with contextualized features derived from large-scale language models.
  arXiv  Detail & Related papers  (2021-06-02T06:49:19Z)
• Aspect-Controlled Neural Argument Generation [65.91772010586605]
  We train a language model for argument generation that can be controlled on a fine-grained level to generate sentence-level arguments for a given topic, stance, and aspect. Our evaluation shows that our generation model is able to generate high-quality, aspect-specific arguments. These arguments can be used to improve the performance of stance detection models via data augmentation and to generate counter-arguments.
  arXiv  Detail & Related papers  (2020-04-30T20:17:22Z)

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.