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» On the practical genetic algorithms
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GECCO
2005
Springer
155views Optimization» more  GECCO 2005»
16 years 5 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
EVOW
2010
Springer
16 years 1 months ago
Evolutionary Algorithm for Generation of Entertaining Shinro Logic Puzzles
A Shinro puzzle is a type of deductive reasoning puzzle that originated in Japanese periodicals. To solve the puzzle, one must locate twelve hidden stones on an 8x8 grid using only...
David Oranchak
IWAN
2000
Springer
15 years 10 months ago
Differentiated Quality of Service in Application Layer Active Networks
A novel approach to quality of service control in an active service network (application layer active network) is described. The approach makes use of a distributed genetic algori...
Chris M. Roadknight, Ian W. Marshall
178
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ICMLA
2007
15 years 8 months ago
Improving gene expression programming performance by using differential evolution
Gene Expression Programming (GEP) is an evolutionary algorithm that incorporates both the idea of a simple, linear chromosome of fixed length used in Genetic Algorithms (GAs) and...
Qiongyun Zhang, Chi Zhou, Weimin Xiao, Peter C. Ne...
CEC
2010
IEEE
15 years 7 months ago
Classifier-assisted constrained evolutionary optimization for automated geometry selection of orthodontic retraction spring
In orthodontics, retraction springs made of metallic wires are often used to move a tooth with respect to another by the virtue of the spring back effect. Specially selected form o...
Dudy Lim, Yew-Soon Ong, Rachman Setiawan, Muhammad...