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CONTEXT
2001
Springer
14 years 4 days ago
A Connectionist-Symbolic Approach to Modeling Agent Behavior: Neural Networks Grouped by Contexts
A recent report by the National Research Council (NRC) declares neural networks “hold the most promise for providing powerful learning models”. While some researchers have expe...
Amy E. Henninger, Avelino J. Gonzalez, Michael Geo...
KBS
2006
231views more  KBS 2006»
13 years 7 months ago
Predicting football results using Bayesian nets and other machine learning techniques
Bayesian networks (BNs) provide a means for representing, displaying, and making available in a usable form the knowledge of experts in a given Weld. In this paper, we look at the...
A. Joseph, Norman E. Fenton, Martin Neil
ICANN
2007
Springer
13 years 9 months ago
Solving Selected Classification Problems in Bioinformatics Using Multilayer Neural Network Based on Multi-Valued Neurons (MLMVN)
A multilayer neural network based on multi-valued neurons (MLMVN) is a new powerful tool for solving classification, recognition and prediction problems. This network has a number ...
Igor N. Aizenberg, Jacek M. Zurada
AUSAI
2006
Springer
13 years 11 months ago
Robust Character Recognition Using a Hierarchical Bayesian Network
There is increasing evidence to suggest that the neocortex of the mammalian brain does not consist of a collection of specialised and dedicated cortical architectures, but instead ...
John Thornton, Torbjorn Gustafsson, Michael Blumen...
ICANN
2010
Springer
13 years 8 months ago
Model of the Hippocampal Learning of Spatio-temporal Sequences
We propose a model of the hippocampus aimed at learning the timed association between subsequent sensory events. The properties of the neural network allow it to learn and predict ...
Julien Hirel, Philippe Gaussier, Mathias Quoy