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GECCO
2008
Springer
110views Optimization» more  GECCO 2008»
13 years 8 months ago
Evolving stable behavior in a spino-neuromuscular system model
This paper demonstrates the effectiveness of genetic algorithms in training stable behavior in a model of the spinoneuromuscular system (SNMS). In particular, we test the stabili...
Stanley Phillips Gotshall, Terry Soule
SOFTCO
2004
Springer
14 years 1 months ago
MultiNNProm: A Multi-Classifier System for Finding Genes
The computational identification of genes in DNA sequences has become an issue of crucial importance due to the large number of DNA molecules being currently sequenced. We present ...
Romesh Ranawana, Vasile Palade
ASC
2004
13 years 7 months ago
Extracting rules from trained neural network using GA for managing E-business
Theabilitytointelligentlycollect,manageandanalyzeinformationaboutcustomersandsellersisakeysourceofcompetitive advantage for an e-business. This ability provides an opportunity to ...
Atta Ebrahim E. ElAlfi, R. Haque, M. Esmel ElAlami
GECCO
2006
Springer
167views Optimization» more  GECCO 2006»
13 years 11 months ago
Genomic computing networks learn complex POMDPs
A genomic computing network is a variant of a neural network for which a genome encodes all aspects, both structural and functional, of the network. The genome is evolved by a gen...
David J. Montana, Eric Van Wyk, Marshall Brinn, Jo...
IWANN
2001
Springer
14 years 3 days ago
A New Approach to Evolutionary Computation: Segregative Genetic Algorithms (SEGA)
This paper looks upon the standard genetic algorithm as an artificial self-organizing process. With the purpose to provide concepts that make the algorithm more open for scalabili...
Michael Affenzeller