Tangming Yuan

Approximating Problems in Abstract Argumentation with Graph Convolutional Networks (Abstract Reprint)

In this article, we present a novel approximation approach for abstract argumentation using a customized Graph Convolutional Network (GCN) architecture and a tailored training method. Our approach demonstrates promising results in approximating abstract argumentation tasks across various semantics,