AIMar 31, 2016

Verifiability of Argumentation Semantics

arXiv:1603.09502v114 citations
Originality Incremental advance
AI Analysis

This work provides a theoretical framework for analyzing and comparing argumentation semantics, which is incremental but contributes to a more abstract understanding in computational argumentation.

The paper tackles the problem of determining the minimal additional information beyond conflict-free sets needed to compute extensions in Dung's argumentation frameworks, introducing a hierarchy of verification classes and showing that standard semantics fit into specific classes.

Dung's abstract argumentation theory is a widely used formalism to model conflicting information and to draw conclusions in such situations. Hereby, the knowledge is represented by so-called argumentation frameworks (AFs) and the reasoning is done via semantics extracting acceptable sets. All reasonable semantics are based on the notion of conflict-freeness which means that arguments are only jointly acceptable when they are not linked within the AF. In this paper, we study the question which information on top of conflict-free sets is needed to compute extensions of a semantics at hand. We introduce a hierarchy of so-called verification classes specifying the required amount of information. We show that well-known standard semantics are exactly verifiable through a certain such class. Our framework also gives a means to study semantics lying inbetween known semantics, thus contributing to a more abstract understanding of the different features argumentation semantics offer.

Foundations

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