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Volumn 3242, Issue , 2004, Pages 912-921

Spatial embedding and loss of gradient in cooperative coevolutionary algorithms

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; OPTIMIZATION; PATHOLOGY;

EID: 33847290404     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-30217-9_92     Document Type: Article
Times cited : (29)

References (19)
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    • Husbands, P., Mill, F.: Simulated coevolution as the mechanism for emergent planning and scheduling. In Belew, R., Booker, L., eds.: Proceedings of the Fourch International Conference on Genetic Algorithms, Morgan Kaufmann (1991) 264-270
    • (1991) Proceedings of the Fourch International Conference on Genetic Algorithms , pp. 264-270
    • Husbands, P.1    Mill, F.2
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    • 10444270597 scopus 로고    scopus 로고
    • Forming neural networks through efficient and adaptive coevolution
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    • (1997) Evolutionary Computation , vol.5 , pp. 373-399
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  • 10
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    • Challenges in Coevolutionary learning: Arms-race dynamics, open-endedness, and mediocre stable states
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    • Ficici, S., Pollack, J.: Challenges in Coevolutionary learning: Arms-race dynamics, open-endedness, and mediocre stable states. In et al, A., ed.: Proceedings of the Sixth International Conference on Artificial Life, Cambridge, MA, MIT Press (1998) 238-247
    • (1998) Proceedings of the Sixth International Conference on Artificial Life , pp. 238-247
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  • 13
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    • Evolutionary games and spatial chaos
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    • (1992) Nature , vol.359 , pp. 826-829
    • Nowak, M.1    May, R.2
  • 15
    • 0000157651 scopus 로고
    • Co-evolving parasites improve simulated evolution as an optimization procedure
    • Hillis, D.: Co-evolving parasites improve simulated evolution as an optimization procedure. Artificial Life II, SFI Studies in the Sciences of Complexity 10 (1991) 313-324
    • (1991) Artificial Life II, SFI Studies in the Sciences of Complexity , vol.10 , pp. 313-324
    • Hillis, D.1
  • 16
    • 85027546455 scopus 로고
    • Distributed Coevolutionary genetic algorithms for multi-criteria and multi-constraint optimisation
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    • Husbands, P.: Distributed Coevolutionary genetic algorithms for multi-criteria and multi-constraint optimisation. In: Evolutionary Computing, AISB Workshop for Selected Papers, Springer-Verlag (1994) 150-165
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    • Ronge, A., Nordahl, M.G.: Genetic programs and co-evolution developing robust general purpose controllers using local mating in two dimensional populations. In Voigt, H.M., Ebeling, W., Rechenberg, I., Schwefel, H.P., eds.: Parallel Problem Solving from Nature IV, Proceedings of the International Conference on Evolutionary Computation. Volume 1141 of LNCS., Berlin, Germany, Springer Verlag (1996) 81-90
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    • Cantú-Paz, E., et al, eds.: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO) 2003. In Cantii-Paz, E., et al, eds.: Berlin, Germany, Springer
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