Balancing quality and quantity in evolving agent systems

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Balancing quality and quantity in evolving agent systems

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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: Artificial life, evolutionary robotics, adaptive behavior, evolvable hardware: posters table of contents

Pages: 335 - 335

Year of Publication: 2007

ISBN:978-1-59593-697-4

Authors

Gusz Eiben	Vrije Universiteit, Amsterdam, Netherlands
Joeri Bekker	Vrije Universiteit, Amsterdam, Netherlands
Robert Griffioen	Vrije Universiteit, Amsterdam, Netherlands
Evert Haasdijk	Universiteit van Tilburg, Tilburg, Netherlands

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): 5, Downloads (12 Months): 19, Citation Count: 0

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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.

N. Gilbert, M. den Besten, A. Bontovics, B. G. Craenen, F. Divina, A. Eiben, R. Griffioen, G. Hévízi, A. Lörincz, B. Paechter, S. Schuster, M. C. Schut, C. Tzolov, P. Vogt, and L. Yang. Emerging artificial societies through learning. Journal of Artificial Societies and Social Simulation, 9(2), 2006.

INDEX TERMS

Primary Classification:
I. Computing Methodologies
I.2 ARTIFICIAL INTELLIGENCE
I.2.11 Distributed Artificial Intelligence
Subjects: Intelligent agents