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» Learning to Map Ontologies with Neural Network
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GECCO
2007
Springer
182views Optimization» more  GECCO 2007»
14 years 1 months ago
Generating large-scale neural networks through discovering geometric regularities
Connectivity patterns in biological brains exhibit many repeating motifs. This repetition mirrors inherent geometric regularities in the physical world. For example, stimuli that ...
Jason Gauci, Kenneth O. Stanley
FLAIRS
2001
13 years 8 months ago
Time Series Analysis Using Unsupervised Construction of Hierarchical Classifiers
Recently we have proposed an algorithm of constructing hierarchical neural network classifiers (HNNC), that is based on a modification of error back-propagation. This algorithm co...
S. A. Dolenko, Yu. V. Orlov, I. G. Persiantsev, Ju...
NN
2002
Springer
115views Neural Networks» more  NN 2002»
13 years 7 months ago
A self-organising network that grows when required
The ability to grow extra nodes is a potentially useful facility for a self-organising neural network. A network that can add nodes into its map space can approximate the input sp...
Stephen Marsland, Jonathan Shapiro, Ulrich Nehmzow
ML
1998
ACM
117views Machine Learning» more  ML 1998»
13 years 7 months ago
Learning Team Strategies: Soccer Case Studies
We use simulated soccer to study multiagent learning. Each team's players (agents) share action set and policy, but may behave di erently due to position-dependent inputs. All...
Rafal Salustowicz, Marco Wiering, Jürgen Schm...
ISCAS
2006
IEEE
119views Hardware» more  ISCAS 2006»
14 years 1 months ago
Using self-organizing maps to control physical robots with omnidirectional drives
— In many application areas, robots most suitably employ classical PID controllers and the like. In the field of autonomous mobile robots, however, further adaptation features a...
Ralf Salomon, Hagen Burchardt, T. Schulz