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If a System is Learning to Self-adapt, Who's Teaching? /
Elkhatib, Yehia; Elhabbash, Abdessalam.
2021 International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS). IEEE, 2021. p. 256-257 9462001 (Proceedings - 2021 International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2021).
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Elkhatib Y, Elhabbash A.
If a System is Learning to Self-adapt, Who's Teaching? In 2021 International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS). IEEE. 2021. p. 256-257. 9462001. (Proceedings - 2021 International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2021). Epub 2021 May 18. doi: 10.1109/SEAMS51251.2021.00043
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Bibtex
@inproceedings{3f0e4cc7ad694dcabbdc4de980f910bd,
title = "If a System is Learning to Self-adapt, Who's Teaching?",
abstract = "Self-adaptation is increasingly driven by machine-learning methods. We argue that the ultimate challenge for self-adaptation currently is to retain the human in the loop just enough to ensure sound evolution of automated self-adaptation.",
author = "Yehia Elkhatib and Abdessalam Elhabbash",
year = "2021",
month = jun,
day = "29",
doi = "10.1109/SEAMS51251.2021.00043",
language = "English",
isbn = "9781665402903",
series = "Proceedings - 2021 International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2021",
publisher = "IEEE",
pages = "256--257",
booktitle = "2021 International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS)",
}
RIS
TY - GEN
T1 - If a System is Learning to Self-adapt, Who's Teaching?
AU - Elkhatib, Yehia
AU - Elhabbash, Abdessalam
PY - 2021/6/29
Y1 - 2021/6/29
N2 - Self-adaptation is increasingly driven by machine-learning methods. We argue that the ultimate challenge for self-adaptation currently is to retain the human in the loop just enough to ensure sound evolution of automated self-adaptation.
AB - Self-adaptation is increasingly driven by machine-learning methods. We argue that the ultimate challenge for self-adaptation currently is to retain the human in the loop just enough to ensure sound evolution of automated self-adaptation.
U2 - 10.1109/SEAMS51251.2021.00043
DO - 10.1109/SEAMS51251.2021.00043
M3 - Conference contribution/Paper
SN - 9781665402903
T3 - Proceedings - 2021 International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2021
SP - 256
EP - 257
BT - 2021 International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS)
PB - IEEE
ER -
