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» Evolving Artificial Neural Networks that Develop in Time
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NN
2002
Springer
115views Neural Networks» more  NN 2002»
14 years 11 months ago
A self-organising network that grows when required
The ability to grow extra nodes is a potentially useful facility for a self-organising neural network. A network that can add nodes into its map space can approximate the input sp...
Stephen Marsland, Jonathan Shapiro, Ulrich Nehmzow
CEC
2007
IEEE
15 years 1 months ago
Multi-population approach to approximate the development of neocortical networks
— Cultured natural cortical neurons form functional networks through a complex set of developmental steps during the first weeks in vitro. The dynamic behavior of the network in...
Andreas Herzog, Karsten Kube, Bernd Michaelis, Ana...
GECCO
2007
Springer
178views Optimization» more  GECCO 2007»
15 years 6 months ago
Nonlinear dynamics modelling for controller evolution
The problem of how to acquire a model of a physical robot, which is fit for evolution of controllers that can subsequently be used to control that robot, is considered in the con...
Julian Togelius, Renzo De Nardi, Hugo Gravato Marq...
NIPS
2008
15 years 1 months ago
Tracking Changing Stimuli in Continuous Attractor Neural Networks
Continuous attractor neural networks (CANNs) are emerging as promising models for describing the encoding of continuous stimuli in neural systems. Due to the translational invaria...
C. C. Alan Fung, K. Y. Michael Wong, Si Wu
CMG
2001
15 years 1 months ago
Software That Can Think and Do
Rapid advances in research and technology now allow data analysis and modeling of extremely complex systems. Methods from artificial intelligence (AI) such as Neural Networks have...
Bernard Domanski