Context-based and explainable decision making with argumentation

• Main Authors: Zeng, Zhiwei, Fan, Xiuyi, Miao, Chunyan, Leung, Cyril, Chin, Jing Jih, Ong, Yew Soon
• Other Authors: Interdisciplinary Graduate School (IGS)
• Format: Conference or Workshop Item
• Language: English
• Published: 2019
• Subjects: Decision Making; Context-awareness; Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
• Online Access: https://hdl.handle.net/10356/88889; http://hdl.handle.net/10220/49589
• Institution: Nanyang Technological University

Argumentation-based approaches to decision making have gained considerable research interest, due to their ability to select and justify decisions. In order to make better decisions, context is a key piece of information that needs to be considered. However, most existing argumentation-based models and frameworks have not modelled or reasoned with context explicitly. In this paper, we present a new argumentation-based approach for making context-based and explainable decisions. We propose a graphical representation for modelling decision problems involving varying contexts, Decision Graphs with Context (DGC), and a reasoning mechanism for making context-based decisions which relies on the Assumption-based Argumentation formalism. Based on these constructs, we introduce two types of explanations, argument explanation and context explanation, identifying the reasons for the decisions made from an argument-view and a context-view respectively.