Complexity results for preference aggregation over (m)CP-nets : Pareto and majority voting
- Submitting institution
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King's College London
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 136476467
- Type
- D - Journal article
- DOI
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10.1016/j.artint.2018.12.010
- Title of journal
- ARTIFICIAL INTELLIGENCE
- Article number
- -
- First page
- 101
- Volume
- 272
- Issue
- -
- ISSN
- 0004-3702
- Open access status
- Compliant
- Month of publication
- January
- Year of publication
- 2019
- 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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1
- Research group(s)
-
-
- Citation count
- 2
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This work, whose preliminary version appeared at AAAI2016, studies the aggregation of combinatorial preferences, needed e.g. in ranking query answers, via Pareto and majority voting, and represented through (m)CP-nets. These problems had been open for ten years and the lack of a precise complexity analysis was raised repeatedly in the literature, before this work closed them. It superseded earlier research relying on heavily restrictive simplifications. The results obtained are a notable leap compared to previous knowledge: from exponential time upperbounds to the polynomial hierarchy or even tractability. This work was also presented in an invited talk at Oxford University.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -