Why is parity hard for estimation of distribution algorithms?

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Why is parity hard for estimation of distribution algorithms?

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Genetic And Evolutionary Computation Conference archive
Proceedings of the 9th annual conference on Genetic and evolutionary computation table of contents

London, England

POSTER SESSION: Estimation of distribution algorithms: posters table of contents

Pages: 624 - 624

Year of Publication: 2007

ISBN:978-1-59593-697-4

Authors

David Jonathan Coffin	University College London, London, United Kingdom
Robert Elliott Smith	University College London, London, United Kingdom

Sponsors

SIGEVO: ACM Special Interest Group on Genetic and Evolutionary Computation
ACM: Association for Computing Machinery

Publisher

ACM New York, NY, USA

Bibliometrics

Downloads (6 Weeks): 1, Downloads (12 Months): 17, Citation Count: 2

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ABSTRACT

We describe a k-bounded and additively separable test problem on which the hierarchical Bayesian Optimization Algorithm (hBOA) scales exponentially.

REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

Pelikan, M., Sastry, K., Butz, M. V., and Goldberg, D. E. Hierarchical boa on random decomposable problems. Technical Report 2006002, IlliGAL, 2006.

CITED BY 2

	David Icǎlnzan , D. Dumitrescu , Béat Hirsbrunner, Correlation guided model building, Proceedings of the 11th Annual conference on Genetic and evolutionary computation, July 08-12, 2009, Montreal, Québec, Canada
	Martin Pelikan , Kumara Sastry , David E. Goldberg , Martin V. Butz , Mark Hauschild, Performance of evolutionary algorithms on NK landscapes with nearest neighbor interactions and tunable overlap, Proceedings of the 11th Annual conference on Genetic and evolutionary computation, July 08-12, 2009, Montreal, Québec, Canada