@inproceedings{a2bf4f9ff37046b1a90296b31007021d,
title = "Symbolic planning with axioms",
abstract = "Axioms are an extension for classical planning models that allow for modeling complex preconditions and goals exponentially more compactly. Although axioms were introduced in planning more than a decade ago, modern planning techniques rarely support axioms, especially in cost-optimal planning. Symbolic search is a popular and competitive optimal planning technique based on the manipulation of sets of states. In this work, we extend symbolic search algorithms to support axioms natively. We analyze different ways of encoding derived variables and axiom rules to evaluate them in a symbolic representation. We prove that all encodings are sound and complete, and empirically show that the presented approach outperforms the previous state of the art in costoptimal classical planning with axioms.",
keywords = "Planning and scheduling",
author = "David Speck and Florian Gei{\ss}er and Robert Mattm{\"u}ller and {\'A}lvaro Torralba",
year = "2019",
language = "English",
series = "Proceedings International Conference on Automated Planning and Scheduling, ICAPS",
pages = "464--472",
editor = "J. Benton and Nir Lipovetzky and Eva Onaindia and Smith, {David E.} and Siddharth Srivastava",
booktitle = "Proceedings of the 29th International Conference on Automated Planning and Scheduling, ICAPS 2019",
publisher = "AAAI Press",
address = "United States",
note = "29th International Conference on Automated Planning and Scheduling, ICAPS 2019 ; Conference date: 11-07-2019 Through 15-07-2019",
}