Stable fractional matchings
- Submitting institution
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The University of Liverpool
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 15844
- Type
- D - Journal article
- DOI
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10.1016/j.artint.2020.103416
- Title of journal
- Artificial Intelligence
- Article number
- 103416
- First page
- -
- Volume
- 0
- Issue
- -
- ISSN
- 0004-3702
- Open access status
- Compliant
- Month of publication
- November
- Year of publication
- 2020
- URL
-
-
- Supplementary information
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- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- 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
- A preliminary version of this paper appeared at the ACM Conference on Economics and Computation (2019). The paper initiates the study of stable fractional matchings, a natural extension of stable matchings, which are ubiquitous in AI, economics, and CS. This direction was swiftly taken up in three follow-up works by Chen et al (arXiv:2011.12259, 2020); Shivika and Narahari (arXiv:2001.05652, 2020); and Shivika et al (arXiv:2009.05823, 2020).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -