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Factored symmetries for merge-and-shrink abstractions

  • University of Basel
  • Technion-Israel Institute of Technology
  • IBM

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

16 Scopus citations

Abstract

Merge-and-shrink heuristics crucially rely on effective reduction techniques, such as bisimulation-based shrinking, to avoid the combinatorial explosion of abstractions. We propose the concept of factored symmetries for merge-andshrink abstractions based on the established concept of symmetry reduction for state-space search. We investigate under which conditions factored symmetry reduction yields perfect heuristics and discuss the relationship to bisimulation. We also devise practical merging strategies based on this concept and experimentally validate their utility.

Original languageEnglish
Title of host publicationProceedings of the 29th AAAI Conference on Artificial Intelligence, AAAI 2015 and the 27th Innovative Applications of Artificial Intelligence Conference, IAAI 2015
PublisherAI Access Foundation
Pages3378-3385
Number of pages8
ISBN (Electronic)9781577357032
StatePublished - 1 Jun 2015
Externally publishedYes
Event29th AAAI Conference on Artificial Intelligence, AAAI 2015 and the 27th Innovative Applications of Artificial Intelligence Conference, IAAI 2015 - Austin, United States
Duration: 25 Jan 201530 Jan 2015

Publication series

NameProceedings of the National Conference on Artificial Intelligence
Volume5

Conference

Conference29th AAAI Conference on Artificial Intelligence, AAAI 2015 and the 27th Innovative Applications of Artificial Intelligence Conference, IAAI 2015
Country/TerritoryUnited States
CityAustin
Period25/01/1530/01/15

Bibliographical note

Publisher Copyright:
© Copyright 2015, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.

Funding

Funders
Israel Science Foundation
Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung

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