@inproceedings{3acb581fee52444fa802cca83ccd43d9,
title = "A state-space acyclicity property for exponentially tighter plan length bounds",
abstract = "We investigate compositional bounding of transition system diameters, with application in bounding the lengths of plans. We establish usefully-tight bounds by exploiting acyclicity in state-spaces. We provide mechanised proofs in HOL4 of the validity of our approach. Evaluating our bounds in a range of benchmarks, we demonstrate exponentially tighter upper bounds compared to existing methods. Treating both solvable and unsolvable benchmark problems, we also demonstrate the utility of our bounds in boosting planner performance. We enhance an existing planning procedure to use our bounds, and demonstrate significant coverage improvements, both compared to the base planner, and also in comparisons with state-of-the-art systems.",
author = "Mohammad Abdulaziz and Charles Gretton and Michael Norrish",
note = "Publisher Copyright: Copyright {\textcopyright} 2017, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.; 27th International Conference on Automated Planning and Scheduling, ICAPS 2017 ; Conference date: 18-06-2017 Through 23-06-2017",
year = "2017",
language = "English",
series = "Proceedings International Conference on Automated Planning and Scheduling, ICAPS",
publisher = "AAAI Press",
pages = "2--10",
editor = "Laura Barbulescu and Smith, {Stephen F.} and Mausam and Frank, {Jeremy D.}",
booktitle = "Proceedings of the 27th International Conference on Automated Planning and Scheduling, ICAPS 2017",
}