Output details
11 - Computer Science and Informatics
University of Portsmouth
Return to search
Output 0 of 0 in the submission
Article title
Autonomous Virulence Adaptation Improves Coevolutionary Optimization
Type
D - Journal article
Title of journal
IEEE Transactions on Evolutionary Computation
Article number
-
Volume number
15
Issue number
2
First page of article
215
ISSN of journal
1941-0026
Year of publication
2011
Number of additional authors
1
Additional information
<22>The paper reports, in a leading AI journal, the problem of population disengagement in co-evolutionary optimisation frameworks. A novel technique, autonomous virulence adaptation (AVA), is presented for tuning the virulence parameter of 2-population competitive genetic algorithm (CGA) systems. Using two classic complex case studies, AVA is shown to offer quality solutions and a significantly reduced computational overhead.
Interdisciplinary
-
Cross-referral requested
-
Research group
None
Citation count
5
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-