Abstract
We investigate knowledge-based self-adaptation in evolutionary programming (EP) using cultural algorithms for 22 function optimization problems. The results suggest that the use of a cultural framework for self-adaptation in EP can produce substantial performance improvements as expressed in terms of CPU time. The nature of these improvements and the type of knowledge that is most effective in producing them will depend on the structure of the problem.
Keywords
Adaptation (eye)Computer scienceEvolutionary programmingCultural algorithmEvolutionary algorithmEvolutionary computationGenetic programmingFunction (biology)Artificial intelligenceMathematical optimizationTheoretical computer scienceGenetic algorithmMachine learningMathematicsMeta-optimizationPsychology
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Publication Info
- Year
- 2002
- Type
- article
- Pages
- 71-76
- Citations
- 51
- Access
- Closed
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Cite This
Robert G. Reynolds,
Chan‐Jin Chung
(2002).
Knowledge-based self-adaptation in evolutionary programming using cultural algorithms.
, 71-76.
https://doi.org/10.1109/icec.1997.592271
Identifiers
- DOI
- 10.1109/icec.1997.592271