Jim Smith James.Smith@uwe.ac.uk
Professor in Interactive Artificial Intelligence
Adaptively parameterised evolutionary systems: Self adaptive recombination and mutation in a genetic algorithm
Smith, Jim; Fogarty, T.C.
Authors
T.C. Fogarty
Contributors
H.-M.~Voigt
Editor
W.~Ebeling
Editor
I.~Rechenberg
Editor
H.-P.~Schwefel
Editor
Citation
Smith, J., & Fogarty, T. Adaptively parameterised evolutionary systems: Self adaptive recombination and mutation in a genetic algorithm. Paper presented at Proceedings of the 4th Conference on Parallel Problem Solving from Nature, Springer, Berlin, Heidelberg, New York
Presentation Conference Type | Conference Paper (unpublished) |
---|---|
Conference Name | Proceedings of the 4th Conference on Parallel Problem Solving from Nature |
Conference Location | Springer, Berlin, Heidelberg, New York |
Publication Date | Jan 1, 1996 |
Peer Reviewed | Not Peer Reviewed |
Pages | 441-450 |
Series Title | Lecture Notes in Computer Science |
Series Number | 1141 |
Keywords | evolutionary systems, genetic algorithms |
Public URL | https://uwe-repository.worktribe.com/output/1106192 |
You might also like
Disclosure control issues in complex medical data
(2023)
Presentation / Conference
SACRO: Semi-Automated Checking Of Research Outputs
(2023)
Presentation / Conference
A novel mirror neuron inspired decision-making architecture for human–robot interaction
(2023)
Journal Article
Inter-annotator agreement using the Conversation Analysis Modelling Schema, for dialogue
(2022)
Journal Article
Downloadable Citations
About UWE Bristol Research Repository
Administrator e-mail: repository@uwe.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search