Output details
11 - Computer Science and Informatics
Robert Gordon University
Article title
Fitness Modelling with Markov Networks
Type
D - Journal article
Title of journal
IEEE Transactions on Evolutionary Computation
Article number
-
Volume number
17
Issue number
6
First page of article
862
ISSN of journal
1089-778X
Year of publication
2013
URL
-
Number of additional authors
2
Additional information
The originality is in providing comprehensive study of Markov Networks (MN) as a general fitness model for discrete problems, extending previous work which was restricted in scope to EDAs (McCall-02). Rigour is demonstrated in showing robust conclusions across a broad range of important benchmarks. The significance is in providing a comprehensively analysed fitness model that can be used on discrete problems, where few alternative approaches are available. The work is published in IEEE TEVC, which is the world-leading journal in evolutionary computation.
Interdisciplinary
-
Cross-referral requested
-
Research group
None
Citation count
-
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-
