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» Evolvable Hardware for Generalized Neural Networks
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GECCO
2009
Springer
14 years 9 days ago
The sensitivity of HyperNEAT to different geometric representations of a problem
HyperNEAT, a generative encoding for evolving artificial neural networks (ANNs), has the unique and powerful ability to exploit the geometry of a problem (e.g., symmetries) by enc...
Jeff Clune, Charles Ofria, Robert T. Pennock
GECCO
2007
Springer
131views Optimization» more  GECCO 2007»
14 years 1 months ago
Using feedback to regulate gene expression in a developmental control architecture
We present what we believe is the first attempt to physically reconstruct the exploratory mechanism of genetic regulatory networks. Feedback plays a crucial role during developme...
Kester Clegg, Susan Stepney, Tim Clarke
CEC
2005
IEEE
14 years 1 months ago
XCS with computed prediction for the learning of Boolean functions
Computed prediction represents a major shift in learning classifier system research. XCS with computed prediction, based on linear approximators, has been applied so far to functi...
Pier Luca Lanzi, Daniele Loiacono, Stewart W. Wils...
GECCO
2007
Springer
178views Optimization» more  GECCO 2007»
14 years 1 months ago
Coevolution of intelligent agents using cartesian genetic programming
A coevolutionary competitive learning environment for two antagonistic agents is presented. The agents are controlled by a new kind of computational network based on a compartment...
Gul Muhammad Khan, Julian Francis Miller, David M....
SIGMETRICS
2008
ACM
115views Hardware» more  SIGMETRICS 2008»
13 years 7 months ago
Densification arising from sampling fixed graphs
During the past decade, a number of different studies have identified several peculiar properties of networks that arise from a diverse universe, ranging from social to computer n...
Pedram Pedarsani, Daniel R. Figueiredo, Matthias G...