Context-based and Explainable Decision Making with Argumentation

Conference Paper/Proceeding/Abstract 1160 views 94 downloads

Zhiwei Zeng, Xiuyi Fan, Chunyan Miao, Cyril Leung, Chin Jing Jih, Ong Yew Soon

Proceedings of the 17th International Conference on Autonomous Agents and Multiagent Systems

Swansea University Author: Xiuyi Fan

Published in:	Proceedings of the 17th International Conference on Autonomous Agents and Multiagent Systems
ISBN:	978-1-4503-5649-7
ISSN:	2523-5699
Published:	Stockholm International conference on Autonomous Agents and Multi-Agent Systems 2018
Online Access:	Check full text
URI:	https://cronfa.swan.ac.uk/Record/cronfa39573
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Item Description:	Originality:In this paper, we present a new argumentation-based approach for making context-based and explainable decisions. We propose a novel graphical representation for modelling decision problems involving varying contexts, Decision Graph with Context (DGC), and a reasoning mechanism for making context-based decisions. We introduce two types of explanations identifying the reasons for decision making.Significance:Argumentation-based decision making has been studied in the past. However, to make suitable decisions, one usually needs to explicitly consider the context information as well. At the same time, making the decision-making process transparent, i.e., realizing “explainable” decision making, is needed to gain trust for any decision-making system. This paper addresses both concerns by introducing DGC and mechanisms for extracting explanations from decision-making processes.Rigor:All results are shown with full proofs. This paper is published in the AAMAS conference, a top conference in artificial intelligence.
Keywords:	Decision making; context-awareness; argumentation; explanation
College:	Faculty of Science and Engineering