Exploratory landscape analysis using algorithm based sampling
Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45) › 32_Refereed conference paper (with ISBN/ISSN) › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
Original language | English |
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Title of host publication | GECCO '18 Proceedings of the Genetic and Evolutionary Computation Conference Companion |
Editors | Hernan Aguirre |
Publisher | ACM New York |
Pages | 211-212 |
ISBN (Electronic) | 978-1-4503-5764-7 |
ISBN (Print) | 9781450357647 |
Publication status | Published - 17 Jul 2018 |
Conference
Title | The Genetic and Evolutionary Computation Conference 2018 |
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Location | |
Place | Japan |
City | Kyoto |
Period | 15 - 19 July 2018 |
Link(s)
Abstract
Exploratory landscape analysis techniques are widely used methods for the algorithm selection problem. The existing sampling methods for exploratory landscape analysis are usually designed to sample unbiased candidates for measuring the characteristics of the entire search space. In this paper, we discuss the limitation of the unbiased sampling and propose a novel sampling method, which is algorithm based and thus biased. Based on the sampling method, we propose several novel landscape features which are called algorithm based landscape features. The proposed features are compared with the conventional landscape features using supervised and unsupervised learning. The experimental results show that the algorithm based landscape features outperform the conventional landscape features.
Research Area(s)
- Algorithm based landscape feature, Algorithm selection, Evolutionary algorithm, Exploratory landscape analysis
Citation Format(s)
Exploratory landscape analysis using algorithm based sampling. / He, Yaodong; Yuen, Shiu Yin ; Lou, Yang.
GECCO '18 Proceedings of the Genetic and Evolutionary Computation Conference Companion. ed. / Hernan Aguirre. ACM New York, 2018. p. 211-212.Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45) › 32_Refereed conference paper (with ISBN/ISSN) › peer-review