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AR
2007
105views more  AR 2007»
15 years 5 months ago
Reinforcement learning of a continuous motor sequence with hidden states
—Reinforcement learning is the scheme for unsupervised learning in which robots are expected to acquire behavior skills through self-explorations based on reward signals. There a...
Hiroaki Arie, Tetsuya Ogata, Jun Tani, Shigeki Sug...
NN
2000
Springer
152views Neural Networks» more  NN 2000»
15 years 4 months ago
A neural network theory of proportional analogy-making
A neural network model that can simulate the learning of some simple proportional analogies is presented. These analogies include, for example, (a) red-square:red-circle yellow-sq...
Nilendu G. Jani, Daniel S. Levine
GECCO
1999
Springer
130views Optimization» more  GECCO 1999»
15 years 9 months ago
Heterochrony and Adaptation in Developing Neural Networks
This paper discusses the simulation results of a model of biological development for neural networks based on a regulatory genome. The model’s results are analyzed using the fra...
Angelo Cangelosi
SAFECOMP
2004
Springer
15 years 10 months ago
Using Fuzzy Self-Organising Maps for Safety Critical Systems
This paper defines a type of constrained artificial neural network (ANN) that enables analytical certification arguments whilst retaining valuable performance characteristics. ...
Zeshan Kurd, Tim Kelly
138
Voted
BMCBI
2010
118views more  BMCBI 2010»
15 years 5 months ago
Artificial neural networks for the prediction of peptide drift time in ion mobility mass spectrometry
Background: There is an increasing usage of ion mobility-mass spectrometry (IMMS) in proteomics. IMMS combines the features of ion mobility spectrometry (IMS) and mass spectrometr...
Bing Wang, Steve Valentine, Manolo Plasencia, Srir...