Memetic Music Composition
- Submitting institution
-
Nottingham Trent University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 23 - 794325
- Type
- D - Journal article
- DOI
-
10.1109/TEVC.2014.2366871
- Title of journal
- IEEE Transactions on Evolutionary Computation
- Article number
- -
- First page
- 1
- Volume
- 20
- Issue
- 1
- ISSN
- 1089-778X
- Open access status
- Out of scope for open access requirements
- Month of publication
- February
- Year of publication
- 2016
- 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
-
3
- Research group(s)
-
A - Computing and Informatics Research Centre
- Citation count
- 14
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The approach proposed proves that AI can exhibit creativity features by learning human capabilities where it can support humans in assembling high-quality musical compositions. There are a growing number of publications highlighting the impact of our research on (i) optimization and (ii) automatic music composition, including DOI: 10.1109/TETCI.2016.2642200 and DOI: 10.1007/s00500-015-1971-3. This output also led to a collaboration with an expert in memetic algorithms (Ong Yew Soon, Nanyang University of Singapore).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
