Strong bounds for evolution in networks
- Submitting institution
-
University of Durham
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 115436
- Type
- D - Journal article
- DOI
-
10.1016/j.jcss.2018.04.004
- Title of journal
- Journal of Computer and System Sciences
- Article number
- -
- First page
- 60
- Volume
- 97
- Issue
- -
- ISSN
- 00220000
- Open access status
- Compliant
- Month of publication
- -
- Year of publication
- 2018
- URL
-
https://doi.org/10.1016/j.jcss.2018.04.004
- 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
-
1
- Research group(s)
-
B - Algorithms and Complexity
- Citation count
- 2
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Embarking from the seminal model for the evolutionary dynamics on graphs by Lieberman, Hauert and Nowak in Nature’05 (https://doi.org/10.1038/nature03204), this paper provided a new and transformative way of thinking about the impact that the underlying graph structure has on the course of evolutionary dynamics. Subsequently to the preliminary conference publication (ICALP’13), the results of the paper have been used by many researchers in world-leading venues in the area, e.g. Nature Scientific Reports 2014 (https://doi.org/10.1038/srep05536), Random Structures and Algorithms 2016 (https://doi.org/10.1002/rsa.20617), Random Structures and Algorithms 2019 (https://doi.org/10.1002/rsa.20890), Nature Scientific Reports 2017 (https://doi.org/10.1038/s41598-017-00107-w), and the Journal of the ACM 2017 (https://doi.org/10.1145/3019609).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -