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GECCO
2005
Springer
155views Optimization» more  GECCO 2005»
16 years 13 days ago
Co-evolving recurrent neurons learn deep memory POMDPs
Recurrent neural networks are theoretically capable of learning complex temporal sequences, but training them through gradient-descent is too slow and unstable for practical use i...
Faustino J. Gomez, Jürgen Schmidhuber
GECCO
2005
Springer
197views Optimization» more  GECCO 2005»
16 years 13 days ago
Performance assessment of an artificial immune system multiobjective optimizer by two improved metrics
In this study, we introduce two improved assessment metrics of multiobjective optimizers, Nondominated Ratio and Spacing Distribution, and analyze their rationality and validity. ...
Maoguo Gong, Licheng Jiao, Haifeng Du, Ronghua Sha...
GECCO
2005
Springer
160views Optimization» more  GECCO 2005»
16 years 13 days ago
Designing resilient networks using a hybrid genetic algorithm approach
As high-speed networks have proliferated across the globe, their topologies have become sparser due to the increased capacity of communication media and cost considerations. Relia...
Abdullah Konak, Alice E. Smith
GECCO
2005
Springer
136views Optimization» more  GECCO 2005»
16 years 13 days ago
Evolutionary computation and the c-value paradox
The C-value Paradox is the name given in biology to the wide variance in and often very large amount of DNA in eukaryotic genomes and the poor correlation between DNA length and p...
Sean Luke
GECCO
2005
Springer
136views Optimization» more  GECCO 2005»
16 years 13 days ago
Incorporating fuzzy knowledge into fitness: multiobjective evolutionary 3D design of process plants
Designing technical plants is a complex and demanding process. It has been shown that the optimization of the simple facility placement problem is already NP-hard. Optimization of...
Ingo Mierswa