Towards Preserving Semantic Structure in Argumentative Multi-Agent via Abstract Interpretation

TL;DR

This paper explores an abstraction approach in dynamic multi-agent argumentation systems to reduce complexity while maintaining the semantic structure, inspired by model-checking techniques.

Contribution

It introduces a novel abstraction method that preserves semantic flow in argumentation frameworks, improving efficiency in multi-agent reasoning.

Findings

Reduced argumentation framework size while preserving semantics

Enhanced computational efficiency in dynamic multi-agent systems

Maintained semantic integrity during abstraction process

Abstract

Over the recent twenty years, argumentation has received considerable attention in the fields of knowledge representation, reasoning, and multi-agent systems. However, argumentation in dynamic multi-agent systems encounters the problem of significant arguments generated by agents, which comes at the expense of representational complexity and computational cost. In this work, we aim to investigate the notion of abstraction from the model-checking perspective, where several arguments are trying to defend the same position from various points of view, thereby reducing the size of the argumentation framework whilst preserving the semantic flow structure in the system.