Towards Preserving Semantic Structure in Argumentative Multi-Agent via Abstract Interpretation
This addresses computational and representational bottlenecks in argumentation for multi-agent systems, though it appears incremental.
The paper tackles the problem of excessive arguments in dynamic multi-agent systems by investigating abstraction from a model-checking perspective to reduce argumentation framework size while preserving semantic structure.
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.