Symmetry breaking in star-topology decoupled search

Daniel Gnad, Álvaro Torralba, Alexander Shleyfman, Jörg Hoffmann

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

12 Scopus citations

Abstract

Symmetry breaking is a well-known method for search reduction. It identifies state-space symmetries prior to search, and prunes symmetric states during search. A recent proposal, star-topology decoupled search, is to search not in the state space, but in a factored version thereof, which avoids the multiplication of states across leaf components in an underlying star-topology structure. We show that, despite the much more complex structure of search states - so-called decoupled states - symmetry breaking can be brought to bear in this framework as well. Starting from the notion of structural symmetries over states, we identify a sub-class of such symmetries suitable for star-topology decoupled search, and we show how symmetries from that sub-class induce symmetry relations over decoupled states. We accordingly extend the routines required for search pruning and solution reconstruction. The resulting combined method can be exponentially better than both its components in theory, and this synergetic advantage is also manifested in practice: empirically, our method reliably inherits the best of its base components, and often outperforms them both.

Original languageEnglish
Title of host publicationProceedings of the 27th International Conference on Automated Planning and Scheduling, ICAPS 2017
EditorsLaura Barbulescu, Stephen F. Smith, Mausam, Jeremy D. Frank
PublisherAAAI press
Pages125-134
Number of pages10
ISBN (Electronic)9781577357896
StatePublished - 2017
Externally publishedYes
Event27th International Conference on Automated Planning and Scheduling, ICAPS 2017 - Pittsburgh, United States
Duration: 18 Jun 201723 Jun 2017

Publication series

NameProceedings International Conference on Automated Planning and Scheduling, ICAPS
ISSN (Print)2334-0835
ISSN (Electronic)2334-0843

Conference

Conference27th International Conference on Automated Planning and Scheduling, ICAPS 2017
Country/TerritoryUnited States
CityPittsburgh
Period18/06/1723/06/17

Bibliographical note

Publisher Copyright:
Copyright © 2017, Association for the Advancement of Artificial Intelligence (www.aaai.org). AH rights reserved.

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