Journal article 913 views 259 downloads
An explainable multi-attribute decision model based on argumentation
Qiaoting Zhong,
Xiuyi Fan,
Xudong Luo,
Francesca Toni
Expert Systems with Applications, Volume: 117, Pages: 42 - 61
Swansea University Author: Xiuyi Fan
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DOI (Published version): 10.1016/j.eswa.2018.09.038
Abstract
An explainable multi-attribute decision model based on argumentation
Published in: | Expert Systems with Applications |
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ISSN: | 09574174 |
Published: |
2019
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Online Access: |
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URI: | https://cronfa.swan.ac.uk/Record/cronfa44264 |
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Item Description: |
Originality:In this paper, we present a multi-attribute decision model and a method for explaining the decisions it recommends based on an argumentative reformulation of the model. Specifically, (i) we define a notion of best decisions amounting to achieving as many goals as possible and exhibiting as few redundant attributes as possible, and (ii) we generate explanations for why a decision is best or better than or as good as another.Significance:Explainability is important to automatic decision-making systems as without a clear understanding of how a recommended decision is generated, it is hard to ensure human trust, debug and improve these systems. By connecting decision making with argumentation, this work provides a mechanism for realizing explainable decision making. Rigor:All results are shown with full proofs. We also conduct an empirical evaluation of our method with legal practitioners, confirming that our method is helpful to understand automatically generated recommendations. |
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Keywords: |
argumentation, decision making, explanation |
Start Page: |
42 |
End Page: |
61 |