Impact Measures for Gradual Argumentation Semantics

TL;DR

This paper refines an existing impact measure and introduces a new one based on Shapley values to better interpret gradual argumentation semantics, supported by a thorough evaluation of their properties.

Contribution

It introduces a novel impact measure rooted in Shapley values and provides a detailed comparison with an existing measure within gradual argumentation semantics.

Findings

The Shapley-based impact measure offers a new perspective on argument influence.

Evaluation principles reveal strengths and limitations of both impact measures.

The analysis enhances understanding of impact measures' desirability in argumentation.

Abstract

Argumentation is a formalism allowing to reason with contradictory information by modeling arguments and their interactions. There are now an increasing number of gradual semantics and impact measures that have emerged to facilitate the interpretation of their outcomes. An impact measure assesses, for each argument, the impact of other arguments on its score. In this paper, we refine an existing impact measure from Delobelle and Villata and introduce a new impact measure rooted in Shapley values. We introduce several principles to evaluate those two impact measures w.r.t. some well-known gradual semantics. This comprehensive analysis provides deeper insights into their functionality and desirability.