Implementing Troubleshooting with Batch Repair
Abstract
Recent work has raised the challenge of efficient automated troubleshooting in domains where repairing a set of components in a single repair action is cheaper than repairing each of them separately. This corresponds to cases where there is a non-negligible overhead to initiating a repair action and to testing the system after a repair action. In this work we propose several algorithms for choosing which batch of components to repair, so as to minimize the overall repair costs. Experimentally, we show the benefit of these algorithms over repairing components one at a time.
Cite
Text
Stern et al. "Implementing Troubleshooting with Batch Repair." AAAI Conference on Artificial Intelligence, 2016. doi:10.1609/AAAI.V30I1.10075Markdown
[Stern et al. "Implementing Troubleshooting with Batch Repair." AAAI Conference on Artificial Intelligence, 2016.](https://mlanthology.org/aaai/2016/stern2016aaai-implementing/) doi:10.1609/AAAI.V30I1.10075BibTeX
@inproceedings{stern2016aaai-implementing,
title = {{Implementing Troubleshooting with Batch Repair}},
author = {Stern, Roni and Kalech, Meir and Shinitzky, Hilla},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2016},
pages = {769-775},
doi = {10.1609/AAAI.V30I1.10075},
url = {https://mlanthology.org/aaai/2016/stern2016aaai-implementing/}
}