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GECCO
2010
Springer
173views Optimization» more  GECCO 2010»
13 years 11 months ago
The baldwin effect in developing neural networks
The Baldwin Effect is a very plausible, but unproven, biological theory concerning the power of learning to accelerate evolution. Simple computational models in the 1980’s gave...
Keith L. Downing
ECAL
1995
Springer
13 years 11 months ago
Evolving Artificial Neural Networks that Develop in Time
Although recently there has been an increasing interest in studing genetically-based development using Artificial Life models, the mapping of the genetic information into the phen...
Stefano Nolfi, Domenico Parisi
FLAIRS
2008
13 years 10 months ago
Evolutionary Learning of Dynamic Naive Bayesian Classifiers
Naive Bayesian classifiers work well in data sets with independent attributes. However, they perform poorly when the attributes are dependent or when there are one or more irrelev...
Miguel A. Palacios-Alonso, Carlos A. Brizuela, Lui...
HAIS
2010
Springer
13 years 10 months ago
Analysing the Low Quality of the Data in Lighting Control Systems
Energy efficiency represents one of the main challenges in the engineering field, i.e., by means of decreasing the energy consumption due to a better design minimising the energy ...
José Ramón Villar, Enrique A. de la ...
CEC
2007
IEEE
13 years 10 months ago
Fitness inheritance in evolutionary and multi-objective high-level synthesis
Abstract—The high-level synthesis process allows the automatic design and implementation of digital circuits starting from a behavioral description. Evolutionary algorithms are v...
Christian Pilato, Gianluca Palermo, Antonino Tumeo...