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GECCO
2005
Springer
153views Optimization» more  GECCO 2005»
13 years 10 months ago
Evolving neural network ensembles for control problems
In neuroevolution, a genetic algorithm is used to evolve a neural network to perform a particular task. The standard approach is to evolve a population over a number of generation...
David Pardoe, Michael S. Ryoo, Risto Miikkulainen
AIIA
2007
Springer
13 years 11 months ago
Evolving Complex Neural Networks
Abstract. Complex networks like the scale-free model proposed by BarabasiAlbert are observed in many biological systems and the application of this topology to artificial neural ne...
Mauro Annunziato, Ilaria Bertini, Matteo De Felice...
APIN
1998
139views more  APIN 1998»
13 years 5 months ago
Evolutionary Learning of Modular Neural Networks with Genetic Programming
Evolutionary design of neural networks has shown a great potential as a powerful optimization tool. However, most evolutionary neural networks have not taken advantage of the fact ...
Sung-Bae Cho, Katsunori Shimohara
ADVCS
2011
251views Database» more  ADVCS 2011»
12 years 5 months ago
Emergent Social Learning Networks in Organizations with Heterogeneous Agents
Two distinct learning mechanisms are considered for a population of agents who engage in decentralized search for the common optimum. An agent may choose to learn via innovation (...
Myong-Hun Chang
GECCO
2007
Springer
174views Optimization» more  GECCO 2007»
13 years 11 months ago
Heuristic speciation for evolving neural network ensemble
Speciation is an important concept in evolutionary computation. It refers to an enhancements of evolutionary algorithms to generate a set of diverse solutions. The concept is stud...
Shin Ando