Size versus truthfulness in the House Allocation problem
- Submitting institution
-
University of Southampton
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 41400064
- Type
- D - Journal article
- DOI
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10.1007/s00453-019-00584-7
- Title of journal
- Algorithmica
- Article number
- -
- First page
- 3422
- Volume
- 81
- Issue
- 9
- ISSN
- 0178-4617
- Open access status
- Compliant
- Month of publication
- May
- Year of publication
- 2019
- URL
-
-
- Supplementary information
-
-
- 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)
-
-
- Citation count
- 0
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Research allocation is one of the most important problems in AI and economics. Incentivising participants to declare their preferences over resources truthfully is of utmost importance in strategic settings. In almost all practical applications it is also highly desirable to allocate as many resources as possible. This is the first work in Computer Science and Economics that addresses the problem of designing a mechanism that ``maximises the size of the allocation’’ conditioned on the mechanism incentivising the agents to report truthfully.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -