Probabilistic interpretations of argumentative attacks: Logical and experimental results1

Author:

Pfeifer Niki1,Fermüller Christian G.2

Affiliation:

1. Department of Philosophy, University of Regensburg, Universitätsstraße 31, 93040 Regensburg, Germany

2. Institute of Logic and Computation, TU Wien, Favoritenstraße 9–11, 1040 Vienna, Austria

Abstract

We present an interdisciplinary approach to argumentation combining logical, probabilistic, and psychological perspectives. We investigate logical attack principles which relate attacks among claims with logical form. For example, we consider the principle that an argument that attacks another argument claiming A triggers the existence of an attack on an argument featuring the stronger claim A ∧ B. We formulate a number of such principles pertaining to conjunctive, disjunctive, negated, and implicational claims. Some of these attack principles seem to be prima facie more plausible than others. To support this intuition, we suggest an interpretation of these principles in terms of coherent conditional probabilities. This interpretation is naturally generalized from qualitative to quantitative principles. Specifically, we use our probabilistic semantics to evaluate the rationality of principles which govern the strength of argumentative attacks. In order to complement our theoretical analysis with an empirical perspective, we present an experiment with students of the TU Vienna ( n = 139) which explores the psychological plausibility of selected attack principles. We also discuss how our qualitative attack principles relate to well-known types of logical argumentation frameworks. Finally, we briefly discuss how our approach relates to the computational argumentation literature.

Publisher

IOS Press

Subject

Artificial Intelligence,Computational Mathematics,Computer Science Applications,Linguistics and Language

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Application of multimodal speech recognition based on deep neural networks in interpretation teaching;Third International Conference on Artificial Intelligence, Virtual Reality, and Visualization (AIVRV 2023);2023-11-08

2. Forecasting with jury-based probabilistic argumentation;Journal of Applied Non-Classical Logics;2023-08-11

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