Does Relaxing Strict Acceptance Condition Improve Test Based Pareto Coevolution?
Abstract
The strict acceptance condition between parent and child is one of the guarantees of monotonic progress in Pareto co-evolution. However, this condition results in "stalling" in progress especially when the cardinality of test set is as large as in the scale of population size in a test based coevolutionary algorithm. We presented two variants of Pareto based Coevolutionary Hill Climber algorithms - rP-PHC-P that relax the strict condition based on competitive shared fitness of non-comparable (parent, child) pairs and fP-PHC-P which relaxes the condition in the form of discarding Pareto dominated candidate solutions regardless of being parent or child as soon as the Pareto front is created. Both of the algorithms improve the progress, are successfully tested for avoiding overspecialization and keep less non-unique candidate solutions in the population slot compare to P-PHC-P.
Publication Date
2-2-2018
Publication Title
2017 IEEE Symposium Series on Computational Intelligence, SSCI 2017 - Proceedings
Volume
2018-January
Number of Pages
1-8
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/SSCI.2017.8285424
Copyright Status
Unknown
Socpus ID
85046130419 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/85046130419
STARS Citation
Golam Bari, A. T.M.; Gaspar, Alessio; Wiegand, R. Paul; and Bucci, Anthony, "Does Relaxing Strict Acceptance Condition Improve Test Based Pareto Coevolution?" (2018). Scopus Export 2015-2019. 7587.
https://stars.library.ucf.edu/scopus2015/7587