liu.seSearch for publications in DiVA
System disruptions
There are recurring service disruptions on some of the search portals due to high traffic. We are working to resolve the issue, you may temporarily encounter an error message.
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Saturated Post-hoc Optimization for Classical Planning
Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering. Univ Basel, Switzerland. (Representation, Learning and Planning)ORCID iD: 0000-0002-2498-8020
Univ Basel, Switzerland.
Univ Basel, Switzerland.
2021 (English)In: Proceedings of the 35th AAAI Conference on Artificial Intelligence, Assoc Advancement Artifical Intelligence , 2021, Vol. 35, p. 11947-11953Conference paper, Published paper (Refereed)
Abstract [en]

Saturated cost partitioning and post-hoc optimization are two powerful cost partitioning algorithms for optimal classical planning. The main idea of saturated cost partitioning is to give each considered heuristic only the fraction of remaining operator costs that it needs to prove its estimates. We show how to apply this idea to post-hoc optimization and obtain a heuristic that dominates the original both in theory and on the IPC benchmarks.

Place, publisher, year, edition, pages
Assoc Advancement Artifical Intelligence , 2021. Vol. 35, p. 11947-11953
Series
AAAI Conference on Artificial Intelligence, ISSN 2159-5399
National Category
Computational Mathematics
Identifiers
URN: urn:nbn:se:liu:diva-179461DOI: 10.1609/aaai.v35i13.17419ISI: 000681269803071ISBN: 9781577358664 (print)OAI: oai:DiVA.org:liu-179461DiVA, id: diva2:1597139
Conference
35th AAAI Conference on Artificial Intelligence, 2021
Note

Funding Agencies|European Research Council (ERC) under the European Unions Horizon 2020 research and innovation programmeEuropean Research Council (ERC) [817639]; TAILOR, a project - EU Horizon 2020 research and innovation programme [952215]

Available from: 2021-09-24 Created: 2021-09-24 Last updated: 2025-11-17

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full text

Search in DiVA

By author/editor
Seipp, Jendrik
By organisation
Artificial Intelligence and Integrated Computer SystemsFaculty of Science & Engineering
Computational Mathematics

Search outside of DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 235 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf