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» Evolving a neural network using dyadic connections
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GECCO
2006
Springer
167views Optimization» more  GECCO 2006»
15 years 1 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
14 years 6 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
14 years 11 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
14 years 11 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
15 years 3 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