Fault-Tolerant Planning under Uncertainty
Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence. Pages 2350-2355.
Abstract
A fault represents some erroneous operation of a system that could result from an action selection error or some abnormal condition. We formally define error models that characterize the likelihood of various faults and consider the problem of fault-tolerant planning, which optimizes performance given an error model. We show that factoring the possibility of errors significantly degrades the performance of stochastic planning algorithms such as LAO*, because the number of reachable states grows dramatically. We introduce an approach to plan for a bounded number of faults and analyze its theoretical properties. When combined with a continual planning paradigm, the k-fault-tolerant planning method can produce near-optimal performance, even when the number of faults exceeds the bound. Empirical results in two challenging domains confirm the effectiveness of the approach in handling different types of runtime errors.
@inproceedings{ijcai2013p346,
title = {Fault-Tolerant Planning under Uncertainty},
author = {Pineda, Luis Enrique and Lu, Yi and Zilberstein, Shlomo and Goldman, Claudia V.},
booktitle = {Proceedings of the Twenty-Third International Joint Conference on
Artificial Intelligence, {IJCAI-13}},
publisher = {AAAI Press / International Joint Conferences on Artificial Intelligence},
editor = {Francesca Rossi},
pages = {2350--2355},
year = {2013},
month = {8},
url = {https://ijcai.org/proceedings/2013/346},
}
TY - CPAPER TI - Fault-Tolerant Planning under Uncertainty AU - Pineda, Luis Enrique AU - Lu, Yi AU - Zilberstein, Shlomo AU - Goldman, Claudia V. T2 - Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence, IJCAI-13 PB - AAAI Press / International Joint Conferences on Artificial Intelligence PY - 2013 SP - 2350 EP - 2355 UR - https://ijcai.org/proceedings/2013/346 ER -Copied
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