Automated Reasoning for City Infrastructure Maintenance Decision Support
Abstract
We present an interactive decision support system for assisting city infrastructure inter-asset management. It combines real-time site specific data retrieval, a knowledge base co-created with domain experts and an inference engine capable of predicting potential consequences and risks resulting from the available data and knowledge. The system can give explanations of each consequence, cope with incomplete and uncertain data by making assumptions about what might be the worst case scenario, and making suggestions for further investigation. This demo presents multiple real-world scenarios, and demonstrates how modifying assumptions (parameter values) can lead to different consequences.
Cite
Text
Wei et al. "Automated Reasoning for City Infrastructure Maintenance Decision Support." International Joint Conference on Artificial Intelligence, 2018. doi:10.24963/IJCAI.2018/868Markdown
[Wei et al. "Automated Reasoning for City Infrastructure Maintenance Decision Support." International Joint Conference on Artificial Intelligence, 2018.](https://mlanthology.org/ijcai/2018/wei2018ijcai-automated/) doi:10.24963/IJCAI.2018/868BibTeX
@inproceedings{wei2018ijcai-automated,
title = {{Automated Reasoning for City Infrastructure Maintenance Decision Support}},
author = {Wei, Lijun and Magee, Derek R. and Dimitrova, Vania and Clarke, Barry and Du, Heshan and Mahesar, Quratul-ain and Al Ammari, Kareem and Cohn, Anthony G.},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2018},
pages = {5877-5879},
doi = {10.24963/IJCAI.2018/868},
url = {https://mlanthology.org/ijcai/2018/wei2018ijcai-automated/}
}