@inproceedings{1a13673d06ff4d848029eebe59861890,
title = "A causal multi-armed bandit approach for domestic robots{\textquoteright} failure avoidance",
abstract = "As there is a growing need for domestic healthcare, multiple projects are aiming to bring domestic robots in our homes. These robots aim to help users in their everyday life through various actions. However, they are subjected to task failure, making them less efficient and, possibly, bothering to the users. In this work, we aim to prevent task failures by understanding their causes through robot{\textquoteright}s experience. In order to guarantee high accuracy, our approach uses highly semantic data as well as user validation. Our approach can consolidate its knowledge or discover new possible causes, and uses a multi-armed bandit solution: R-UCB. In order to make it more efficient, R-UCB was improved using causal induction and causal graphs. Experiments show our proposition to achieve a very high rate of correct failure prevention.",
keywords = "Domestic robotics, Experience, Multi-armed bandit, Ontologies, Reasoning, Task failure",
author = "Nathan Ramoly and Amel Bouzeghoub and Beatrice Finance",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2017.; 24th International Conference on Neural Information Processing, ICONIP 2017 ; Conference date: 14-11-2017 Through 18-11-2017",
year = "2017",
month = jan,
day = "1",
doi = "10.1007/978-3-319-70136-3\_10",
language = "English",
isbn = "9783319701356",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "90--99",
editor = "Derong Liu and Shengli Xie and Dongbin Zhao and Yuanqing Li and El-Alfy, \{El-Sayed M.\}",
booktitle = "Neural Information Processing - 24th International Conference, ICONIP 2017, Proceedings",
}