On creating complementary pattern databases
- Submitting institution
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The University of Huddersfield
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 46
- Type
- E - Conference contribution
- DOI
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10.24963/ijcai.2017/601
- Title of conference / published proceedings
- Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI-17)
- First page
- 4302
- Volume
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- Issue
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- ISSN
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- Open access status
- -
- Month of publication
- August
- Year of publication
- 2017
- URL
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- Supplementary information
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- Request cross-referral to
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- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
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- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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3
- Research group(s)
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- Citation count
- -
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Pattern database (PDB) in planning is a lookup table containing optimal solution costs of a simplified version of the task. At a given iteration, our method uses estimates of the A* running time to create a PDB that complements the strengths of PDBs created in previous iterations. The research was funded by an international collaboration supported by three research grants AOARD, CAPES and BMBF-CISPA. This PDB was used as the the basis of the “Complementary” planning engine and was awarded Runner-up in the Optimal Planning Track (ICAPS 2018 International Planning Competition) (https://ipc2018-classical.bitbucket.io/ for results) and best performing non-portfolio-based planner (https://planning.wiki/_citedpapers/planners/complementary2.pdf)
- Author contribution statement
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- Non-English
- No
- English abstract
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