Compiling Away Uncertainty in Strong Temporal Planning with Uncontrollable Durations
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence. Main Track. Pages 1631-1636.
Abstract
Real world temporal planning often involves dealing with uncertainty about the duration of actions. In this paper, we describe a sound-and-complete compilation technique for strong planning that reduces any planning instance with uncertainty in the duration of actions to a plain temporal planning problem without uncertainty. We evaluate our technique by comparing it with a recent technique for PDDL domains with temporal uncertainty. The experimental results demonstrate the practical applicability of our approach and show complementary behavior with respect to previous techniques. We also demonstrate the high expressiveness of the translation by applying it to a significant fragment of the ANML language.
@inproceedings{ijcai2015p233,
title = {Compiling Away Uncertainty in Strong Temporal Planning with Uncontrollable Durations},
author = {Micheli, Andrea and Do, Minh and Smith, David E.},
booktitle = {Proceedings of the Twenty-Fourth International Joint Conference on
Artificial Intelligence, {IJCAI-15}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Qiang Yang and Michael Wooldridge},
pages = {1631--1636},
year = {2015},
month = {7},
note = {Main Track},
url = {https://ijcai.org/proceedings/2015/233},
}
TY - CPAPER TI - Compiling Away Uncertainty in Strong Temporal Planning with Uncontrollable Durations AU - Micheli, Andrea AU - Do, Minh AU - Smith, David E. T2 - Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-15 PB - International Joint Conferences on Artificial Intelligence PY - 2015 SP - 1631 EP - 1636 UR - https://ijcai.org/proceedings/2015/233 ER -Copied
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