# Aggregation in Value-Based Argumentation Frameworks

## TL;DR

This paper examines how to aggregate diverse value-based argumentation frameworks from multiple agents, comparing value aggregation, attack relation aggregation, and a novel ranking aggregation approach to achieve collective agreement.

## Contribution

It introduces a third aggregation method based on ranking extraction and analyzes the strengths and limitations of existing approaches in multi-agent argumentation.

## Key findings

- Comparison of value and attack aggregation approaches
- Proposal of a ranking-based aggregation method
- Analysis of collective decision-making in argumentation frameworks

## Abstract

Value-based argumentation enhances a classical abstract argumentation graph - in which arguments are modelled as nodes connected by directed arrows called attacks - with labels on arguments, called values, and an ordering on values, called audience, to provide a more fine-grained justification of the attack relation. With more than one agent facing such an argumentation problem, agents may differ in their ranking of values. When needing to reach a collective view, such agents face a dilemma between two equally justifiable approaches: aggregating their views at the level of values, or aggregating their attack relations, remaining therefore at the level of the graphs. We explore the strenghts and limitations of both approaches, employing techniques from preference aggregation and graph aggregation, and propose a third possibility aggregating rankings extracted from given attack relations.