Proposal and Evaluation of Functionally Specialized CMA-ES
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- Akimoto Youhei
- Tokyo Institute of Technology
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- Sakuma Jun
- Tokyo Institute of Technology
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- Ono Isao
- Tokyo Institute of Technology
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- Kobayashi Shigenobu
- Tokyo Institute of Technology
Bibliographic Information
- Other Title
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- 機能分担CMA-ESの提案と評価
Abstract
This paper aims the design of efficient and effective optimization algorithms for function optimization. For that purpose we present a new framework of the derandomized evolution strategy with covariance matrix adaptation, which combines the hybrid step size adaptation that is proposed in this paper as a robust alternate to the cumulative step size adaptation and normalization mechanism of covariance matrix. Experiment is conducted on 8 classical unimodal and multimodal test functions and the performance of the proposed strategy is compared with that of the standard strategy. Results show that the proposed strategy beats the standard strategy when the population size becomes larger than the default one, while the performance of proposed strategy is as well or better than that of the standard strategy under the default population size.
Journal
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- Transactions of the Japanese Society for Artificial Intelligence
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Transactions of the Japanese Society for Artificial Intelligence 24 (1), 58-68, 2009
The Japanese Society for Artificial Intelligence
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Keywords
Details 詳細情報について
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- CRID
- 1390001205106310528
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- NII Article ID
- 130000098270
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- ISSN
- 13468030
- 13460714
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- Text Lang
- ja
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- Data Source
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- JaLC
- Crossref
- CiNii Articles
- KAKEN
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- Abstract License Flag
- Disallowed