Title
Explainable and Contextual Preferences based Decision Making with Assumption-based Argumentation for Diagnostics and Prognostics of Alzheimer's Disease
Abstract
We present an argumentation-based approach to decision making that can support context-based defeasible preferences and offer dialogical explanations for the decisions made. The proposed approach makes and explains a decision as follows: (1) construct a Contextual Preference Decision Framework (CPDF) to model the problem, (2) use Assumption-based Argumentation as a sound and complete computational mechanism for identifying most-contextual-preferred decisions in the CPDF, and (3) construct explaining dialogues to provide dialogical explanations for identified decisions. We have implemented our approach for two tasks, diagnostics and prognostics of Alzheimer's Disease (AD), and evaluated the performance of our models on the two tasks with real-world datasets.
Year
DOI
Venue
2020
10.5555/3398761.3399078
AAMAS '19: International Conference on Autonomous Agents and Multiagent Systems Auckland New Zealand May, 2020
DocType
ISBN
Citations 
Conference
978-1-4503-7518-4
0
PageRank 
References 
Authors
0.34
0
7
Name
Order
Citations
PageRank
Zhiwei Zeng155.58
Zhiqi Shen253.77
Jing Jih Chin3132.92
Cyril Leung489962.23
Yu Wang525513.80
Ying Chi602.03
Chunyan Miao72307195.72