Publication

Handling unforeseen failures using argumentation-based learning

Ayoobi, H., Cao, M., Verbrugge, L. & Verheij, B., 1-Aug-2019, International Conference on Automation Science and Engineering (CASE) 2019. IEEE Computer Society, p. 1699-1704 6 p. (IEEE International Conference on Automation Science and Engineering; vol. 2019-August).

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

APA

Ayoobi, H., Cao, M., Verbrugge, L., & Verheij, B. (2019). Handling unforeseen failures using argumentation-based learning. In International Conference on Automation Science and Engineering (CASE) 2019 (pp. 1699-1704). (IEEE International Conference on Automation Science and Engineering; Vol. 2019-August). IEEE Computer Society. https://doi.org/10.1109/COASE.2019.8843207

Author

Ayoobi, Hamed ; Cao, Ming ; Verbrugge, Laurina ; Verheij, Bart. / Handling unforeseen failures using argumentation-based learning. International Conference on Automation Science and Engineering (CASE) 2019. IEEE Computer Society, 2019. pp. 1699-1704 (IEEE International Conference on Automation Science and Engineering).

Harvard

Ayoobi, H, Cao, M, Verbrugge, L & Verheij, B 2019, Handling unforeseen failures using argumentation-based learning. in International Conference on Automation Science and Engineering (CASE) 2019. IEEE International Conference on Automation Science and Engineering, vol. 2019-August, IEEE Computer Society, pp. 1699-1704, 15th IEEE International Conference on Automation Science and Engineering, CASE 2019, Vancouver, Canada, 22/08/2019. https://doi.org/10.1109/COASE.2019.8843207

Standard

Handling unforeseen failures using argumentation-based learning. / Ayoobi, Hamed; Cao, Ming; Verbrugge, Laurina; Verheij, Bart.

International Conference on Automation Science and Engineering (CASE) 2019. IEEE Computer Society, 2019. p. 1699-1704 (IEEE International Conference on Automation Science and Engineering; Vol. 2019-August).

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Vancouver

Ayoobi H, Cao M, Verbrugge L, Verheij B. Handling unforeseen failures using argumentation-based learning. In International Conference on Automation Science and Engineering (CASE) 2019. IEEE Computer Society. 2019. p. 1699-1704. (IEEE International Conference on Automation Science and Engineering). https://doi.org/10.1109/COASE.2019.8843207


BibTeX

@inproceedings{144da5ffc3d54eefafc2ad18513834de,
title = "Handling unforeseen failures using argumentation-based learning",
abstract = "General Purpose Service Robots operate in different environments of a dynamic nature. Even the robot's programmer cannot predict what kind of failure conditions a robot may confront in its lifetime. Therefore, general purpose service robots need to efficiently handle unforeseen failure conditions. Thisrequires the capability of handling unforeseen failures while the robot is performing a task. Existing research typically offers special-purpose solutions depending on what has beenforeseen at the design time. In this research, we propose a general purpose argumentation-based architecture which is able to autonomously recoverfrom unforeseen failures. We compare the proposed method with existing incremental online learning methods in the literature. The results show that the proposed argumentation-based learning approach is capable of learning complex scenarios with higher precision than other methods.",
author = "Hamed Ayoobi and Ming Cao and Laurina Verbrugge and Bart Verheij",
year = "2019",
month = aug,
day = "1",
doi = "10.1109/COASE.2019.8843207",
language = "English",
isbn = "9781728103563",
series = "IEEE International Conference on Automation Science and Engineering",
publisher = "IEEE Computer Society",
pages = "1699--1704",
booktitle = "International Conference on Automation Science and Engineering (CASE) 2019",
note = "15th IEEE International Conference on Automation Science and Engineering, CASE 2019 ; Conference date: 22-08-2019 Through 26-08-2019",

}

RIS

TY - GEN

T1 - Handling unforeseen failures using argumentation-based learning

AU - Ayoobi, Hamed

AU - Cao, Ming

AU - Verbrugge, Laurina

AU - Verheij, Bart

PY - 2019/8/1

Y1 - 2019/8/1

N2 - General Purpose Service Robots operate in different environments of a dynamic nature. Even the robot's programmer cannot predict what kind of failure conditions a robot may confront in its lifetime. Therefore, general purpose service robots need to efficiently handle unforeseen failure conditions. Thisrequires the capability of handling unforeseen failures while the robot is performing a task. Existing research typically offers special-purpose solutions depending on what has beenforeseen at the design time. In this research, we propose a general purpose argumentation-based architecture which is able to autonomously recoverfrom unforeseen failures. We compare the proposed method with existing incremental online learning methods in the literature. The results show that the proposed argumentation-based learning approach is capable of learning complex scenarios with higher precision than other methods.

AB - General Purpose Service Robots operate in different environments of a dynamic nature. Even the robot's programmer cannot predict what kind of failure conditions a robot may confront in its lifetime. Therefore, general purpose service robots need to efficiently handle unforeseen failure conditions. Thisrequires the capability of handling unforeseen failures while the robot is performing a task. Existing research typically offers special-purpose solutions depending on what has beenforeseen at the design time. In this research, we propose a general purpose argumentation-based architecture which is able to autonomously recoverfrom unforeseen failures. We compare the proposed method with existing incremental online learning methods in the literature. The results show that the proposed argumentation-based learning approach is capable of learning complex scenarios with higher precision than other methods.

UR - http://www.scopus.com/inward/record.url?scp=85072985953&partnerID=8YFLogxK

U2 - 10.1109/COASE.2019.8843207

DO - 10.1109/COASE.2019.8843207

M3 - Conference contribution

AN - SCOPUS:85072985953

SN - 9781728103563

T3 - IEEE International Conference on Automation Science and Engineering

SP - 1699

EP - 1704

BT - International Conference on Automation Science and Engineering (CASE) 2019

PB - IEEE Computer Society

T2 - 15th IEEE International Conference on Automation Science and Engineering, CASE 2019

Y2 - 22 August 2019 through 26 August 2019

ER -

ID: 77240091