On the effective configuration of planning domain models
- Submitting institution
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The University of Huddersfield
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 50
- Type
- E - Conference contribution
- DOI
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- Title of conference / published proceedings
- IJCAI 2015 - Proceedings of the 24th International Joint Conference on Artificial Intelligence
- First page
- 1704
- Volume
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- Issue
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- ISSN
- -
- Open access status
- -
- Month of publication
- July
- Year of publication
- 2015
- 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
- 6
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper is one of the first works in automated reasoning to show empirically that knowledge configuration choice has a significant impact on the reasoning process. Vallati’s subsequent works (in AI*IA 2019, ICAPS 2018, SOCS 2017, IJAR 2017, COMMA 2016) have investigated different approaches to determining the configuration, or applying it to different areas of AI, such as argumentation. This configuration approach is now routinely exploited by research groups (e.g. in the University of Tokyo https://jair.org/index.php/jair/article/view/11039), and was used as the basis for Frank Hutter’s (Head of ML lab at Freiburg) invited talk to ICAPS 2020 https://www.youtube.com/watch?v=9-3ck0FO19Y
- Author contribution statement
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- Non-English
- No
- English abstract
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