85 search results - page 5 / 17 » A Note on Learning and Evolution in Neural Networks |
TNN
1998
13 years 6 months ago
1998
— In this paper, we perform a complete asymptotic performance analysis of the stochastic approximation algorithm (denoted subspace network learning algorithm) derived from Oja’...
FLAIRS
2003
13 years 8 months ago
2003
Neural-symbolic integration concerns the integration of symbolic and connectionist systems. Distributed knowledge representation is traditionally seen under a purely symbolic pers...
GECCO
2010
Springer
13 years 10 months ago
2010
Springer
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...
SAB
2010
Springer
13 years 5 months ago
2010
Springer
Biological brains can adapt and learn from past experience. In neuroevolution, i.e. evolving artificial neural networks (ANNs), one way that agents controlled by ANNs can evolve t...
EELC
2006
13 years 10 months ago
2006
We present a neural-competitive learning model of language evolution in which several symbol sequences compete to signify a given propositional meaning. Both symbol sequences and p...