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A coevolution archive based on problem dimension
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Genetic And Evolutionary Computation Conference archive
Proceedings of the 10th annual conference on Genetic and evolutionary computation table of contents
Atlanta, GA, USA
POSTER SESSION: Coevolution posters table of contents
Pages 389-390  
Year of Publication: 2008
ISBN:978-1-60558-130-9
Authors
Liping Yang  Beijing Jiaotong University, Beijing, China
Houkuan Huang  Beijing Jiaotong University, Beijing, China
Yabin Liu  Shandong University of Finance, Jinan, China
Sponsors
ACM: Association for Computing Machinery
SIGEVO: ACM Special Interest Group on Genetic and Evolutionary Computation
Publisher
ACM  New York, NY, USA
Bibliometrics
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Additional Information:

abstract   references   index terms   collaborative colleagues  

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ABSTRACT

Recent work has shown the existence of an implicit dimension structure within coevolution problems, which can uniquely determine the overall performance of a individual. In this paper, we present a reliable dimension identifying method. Based on this , we put forward a suitable archive scheme, which maintains only the most representative individuals in terms of problem dimensional information identified during coevolution, and achieves minimum size while guaranteeing monotonic progress. The experimental results on COMPARE-ON-ONE and COMPARE-ON-ALL demonstrate the viability of the algorithm


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.

 
1
Bucci, A. and Pollack, J. B. Focusing versus intransitivity: Geometrical aspects of coevolution. GECCO -03. 250--261
 
2
De Jong, E.D. The Incremental Pareto-Coevolution Archive. GECCO-04, 525--536.
 
3
De Jong, E.D. Towards a bounded Pareto-Coevolution archive. CEC-04. 2341--2348.

INDEX TERMS

Primary Classification:
  F. Theory of Computation
  F.0 GENERAL


General Terms:
Algorithms, Experimentation, Performance, Reliability


Keywords:
archive, coevolution, dimension, reliability, structure-archive

Collaborative Colleagues:
Liping Yang: colleagues
Houkuan Huang: colleagues
Yabin Liu: colleagues

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