Generalized Planning: Synthesizing Plans that Work for Multiple Environments
Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence. Pages 918-922.
Abstract
We give a formal definition of generalized planning that is independent of any representation formalism. We assume that our generalized plans must work on a set of deterministic environments, which are essentially unrelated to each other. We prove that generalized planning for a finite set of environments is always decidable and EXPSPACE-complete. Our proof is constructive and gives us a sound, complete and complexity-wise optimal technique. We also consider infinite sets of environments, and show that generalized planning for the infinite one-dimensional problems, known in the literature to be recursively enumerable when restricted to finite-state plans, is EXPSPACE-decidable without sequence functions, and solvable by generalized planning for finite sets.
@inproceedings{ijcai2011p159,
title = {Generalized Planning: Synthesizing Plans that Work for Multiple Environments},
author = {Hu, Yuxiao and De Giacomo, Giuseppe},
booktitle = {Proceedings of the Twenty-Second International Joint Conference on
Artificial Intelligence, {IJCAI-11}},
publisher = {AAAI Press/International Joint Conferences on Artificial Intelligence},
editor = {Toby Walsh},
pages = {918--922},
year = {2011},
month = {7},
doi = {10.5591/978-1-57735-516-8/IJCAI11-159},
url = {https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-159},
}
TY - CPAPER TI - Generalized Planning: Synthesizing Plans that Work for Multiple Environments AU - Hu, Yuxiao AU - De Giacomo, Giuseppe T2 - Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence, IJCAI-11 PB - AAAI Press/International Joint Conferences on Artificial Intelligence PY - 2011 SP - 918 EP - 922 DO - 10.5591/978-1-57735-516-8/IJCAI11-159 UR - https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-159 ER -Copied
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