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» Evolving Complex Neural Networks
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GECCO
2007
Springer
158views Optimization» more  GECCO 2007»
15 years 4 months ago
A novel generative encoding for exploiting neural network sensor and output geometry
A significant problem for evolving artificial neural networks is that the physical arrangement of sensors and effectors is invisible to the evolutionary algorithm. For example,...
David B. D'Ambrosio, Kenneth O. Stanley
EVOW
2008
Springer
14 years 11 months ago
Scaffolding for Interactively Evolving Novel Drum Tracks for Existing Songs
Abstract. A major challenge in computer-generated music is to produce music that sounds natural. This paper introduces NEAT Drummer, which takes steps toward natural creativity. NE...
Amy K. Hoover, Michael P. Rosario, Kenneth O. Stan...
IJNS
2000
80views more  IJNS 2000»
14 years 9 months ago
VLSI Implementation of Neural Networks
Currently, fuzzy controllers are the most popular choice for hardware implementation of complex control surfaces because they are easy to design. Neural controllers are more compl...
Bogdan M. Wilamowski, J. Binfet, M. O. Kaynak
SAB
2010
Springer
117views Optimization» more  SAB 2010»
14 years 8 months ago
Indirectly Encoding Neural Plasticity as a Pattern of Local Rules
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...
Sebastian Risi, Kenneth O. Stanley
ICPR
2008
IEEE
15 years 11 months ago
Unsupervised design of Artificial Neural Networks via multi-dimensional Particle Swarm Optimization
In this paper, we present a novel and efficient approach for automatic design of Artificial Neural Networks (ANNs) by evolving to the optimal network configuration(s) within an ar...
E. Alper Yildirim, Ince Turker, Moncef Gabbouj, Se...