An Interaction Model for Merging Multi-Agent Argumentation in Shared Clinical Decision Making

Shengxin Hong, Liang Xiao, Jianxia Chen

Abstract: In today’s complex healthcare environment, shared decision making is increasingly being emphasized as an ideal model for healthcare decision making. The interaction of a set of arguments can represent the beliefs of agents, and the process of reaching consensus in a multi-agent system can be facilitated by argument merging. However, existing argumentation models are insufficient to support the application of shared decision making in healthcare. To fill this gap, this paper, we construct a cognitive representation model of agents supporting the computational task of argumentation and propose a novel interactive argumentation framework merging method based on it as a solution for shared decision support in healthcare environment. We used the Lightweight Social Calculus (LSC) to describe and standardize our interaction model. The usability of the method is demonstrated by definitional proofs and case study.