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» Evolving a neural network using dyadic connections
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GECCO
2006
Springer
167views Optimization» more  GECCO 2006»
13 years 11 months ago
Genomic computing networks learn complex POMDPs
A genomic computing network is a variant of a neural network for which a genome encodes all aspects, both structural and functional, of the network. The genome is evolved by a gen...
David J. Montana, Eric Van Wyk, Marshall Brinn, Jo...
AINA
2010
IEEE
13 years 4 months ago
Neural Network Trainer through Computer Networks
- This paper introduces a neural network training tool through computer networks. The following algorithms, such as neuron by neuron (NBN) [1][2], error back propagation (EBP), Lev...
Nam Pham, Hao Yu, Bogdan M. Wilamowski
CEC
2005
IEEE
13 years 9 months ago
Graph composition in a graph grammar-based method for automata network evolution
The dynamics of neural and other automata networks are defined to a large extent by their topologies. Artificial evolution constitutes a practical means by which an optimal topolog...
Martin H. Luerssen, David M. W. Powers
NIPS
1998
13 years 9 months ago
Computational Differences between Asymmetrical and Symmetrical Networks
Symmetrically connected recurrent networks have recently been used as models of a host of neural computations. However, biological neural networks have asymmetrical connections, at...
Zhaoping Li, Peter Dayan
IJCNN
2006
IEEE
14 years 1 months ago
A Very Small Chaotic Neural Net
— Previously we have shown that chaos can arise in networks of physically realistic neurons [1], [2]. Those networks contain a moderate to large number of units connected in a sp...
Carlos Lourenco