Explained Activity Recognition with Computational Assumption-Based Argumentation

被引：3

作者：

Fan, Xiuyi ^{[1
]}

Liu, Siyuan ^{[1
]}

Zhang, Huiguo ^{[1
]}

Leung, Cyril ^{[2
]}

Miao, Chunyan ^{[1
]}

机构：

[1] Nanyang Technol Univ, Joint NTU UBC Res Ctr Excellence Act Living Elder, Singapore, Singapore

[2] Univ British Columbia, Elect & Comp Engn, Vancouver, BC V5Z 1M9, Canada

来源：

ECAI 2016: 22ND EUROPEAN CONFERENCE ON ARTIFICIAL INTELLIGENCE | 2016年 / 285卷

关键词：

D O I：

10.3233/978-1-61499-672-9-1590

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Activity recognition is a key problem in multi-sensor systems. In this work, we introduce Computational Assumption-based Argumentation, an argumentation approach that seamlessly combines sensor data processing with high-level inference. Our method gives classification results comparable to machine learning based approaches with reduced training time while also giving explanations.

引用

页码：1590 / 1591

页数：2

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