An explainable multi-attribute decision model based on argumentation

作者：

Highlights：

• Selecting decisions that achieve most goals but with fewest redundant attributes.

• An argumentative process to identify best decisions with explanation.

• Application in literature search in law shows promising results.

• Natural language explanations are useful for supporting human decision makers.

摘要

•Selecting decisions that achieve most goals but with fewest redundant attributes.•An argumentative process to identify best decisions with explanation.•Application in literature search in law shows promising results.•Natural language explanations are useful for supporting human decision makers.

论文关键词：Multi-attribute decision-making,Explainable artificial intelligence,Computational argumentation,Natural language generation

论文评审过程：Received 10 April 2018, Revised 16 September 2018, Accepted 17 September 2018, Available online 21 September 2018, Version of Record 27 September 2018.

论文官网地址：https://doi.org/10.1016/j.eswa.2018.09.038