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» On the Use of Evidence in Neural Networks
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TNN
1998
92views more  TNN 1998»
15 years 1 months ago
Inductive inference from noisy examples using the hybrid finite state filter
—Recurrent neural networks processing symbolic strings can be regarded as adaptive neural parsers. Given a set of positive and negative examples, picked up from a given language,...
Marco Gori, Marco Maggini, Enrico Martinelli, Giov...
GECCO
2010
Springer
152views Optimization» more  GECCO 2010»
15 years 6 months ago
Importing the computational neuroscience toolbox into neuro-evolution-application to basal ganglia
Neuro-evolution and computational neuroscience are two scientific domains that produce surprisingly different artificial neural networks. Inspired by the “toolbox” used by ...
Jean-Baptiste Mouret, Stéphane Doncieux, Be...
NN
2000
Springer
128views Neural Networks» more  NN 2000»
15 years 1 months ago
A recurrent neural network for solving linear projection equations
Linear projection equations arise in many optimization problems and have important applications in science and engineering. In this paper, we present a recurrent neural network fo...
Youshen Xia, Jun Wang
CONTEXT
2001
Springer
15 years 6 months 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...
COGSCI
2011
108views more  COGSCI 2011»
14 years 8 months ago
The AHA! Experience: Creativity Through Emergent Binding in Neural Networks
Many kinds of creativity result from combination of mental representations. This paper provides a computational account of how creative thinking can arise from combining neural pa...
Paul Thagard, Terrence C. Stewart