期刊
INTERNATIONAL JOURNAL OF APPROXIMATE REASONING
卷 146, 期 -, 页码 79-105出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.ijar.2022.04.003
关键词
Computational argumentation; Probabilistic argumentation; Argument strength
This paper focuses on one aspect of argument strength in deductive argumentation based on defeasible logic. It investigates various ways to calculate argument strength based on the probabilistic necessity and sufficiency of the premises, as well as competing premises and claims. The study provides axioms and explores four specific probability-based measures.
It is common for people to remark that a particular argument is a strong (or weak) argument. Having a handle on the relative strengths of arguments can help in deciding on which arguments to consider, which arguments to regard as acceptable, and on which arguments to present to others in a discussion. In computational models of argument, there is a need for a deeper understanding of argument strength. It is a multidimensional problem, and in this paper, we focus on one aspect of argument strength for deductive argumentation based on a defeasible logic. We assume a probability distribution over models of the language and consider how there are various ways to calculate argument strength based on the probabilistic necessity and sufficiency of the premises for the claim, the probabilistic sufficiency of competing premises the claim, and the probabilistic necessity of the premises for competing claims. We provide axioms for characterizing probability-based measures of argument strength, and we investigate four specific probability-based measures. (c) 2022 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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