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» The baldwin effect in developing neural networks
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CMG
2001
13 years 9 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
JUCS
2010
150views more  JUCS 2010»
13 years 6 months ago
SOM Clustering to Promote Interoperability of Directory Metadata: A Grid-Enabled Genetic Algorithm Approach
: Directories provide a general mechanism for describing resources and enabling information sharing within and across organizations. Directories must resolve differing structures a...
Lei Li, Vijay K. Vaishnavi, Art Vandenberg
ATAL
2005
Springer
14 years 1 months ago
Improving reinforcement learning function approximators via neuroevolution
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
Shimon Whiteson
NIPS
2008
13 years 9 months ago
Non-stationary dynamic Bayesian networks
Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
Joshua W. Robinson, Alexander J. Hartemink
ECCV
2000
Springer
14 years 9 months ago
Non-linear Bayesian Image Modelling
In recent years several techniques have been proposed for modelling the low-dimensional manifolds, or `subspaces', of natural images. Examples include principal component anal...
Christopher M. Bishop, John M. Winn