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» Explanation-Based Neural Network Learning for Robot Control
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IJCNN
2006
IEEE
15 years 5 months ago
Venn-like models of neo-cortex patches
— This work presents a new architecture of artificial neural networks – Venn Networks, which produce localized activations in a 2D map while executing simple cognitive tasks. T...
Fernando Buarque de Lima Neto, Philippe De Wilde
ICANN
2009
Springer
15 years 4 months ago
Learning Complex Population-Coded Sequences
The sequential structure of complex actions is apparently at an abstract “cognitive” level in several regions of the frontal cortex, independent of the control of the immediate...
Kiran V. Byadarhaly, Mithun Perdoor, Suresh Vasa, ...
ICANN
2010
Springer
15 years 24 days ago
Exploring Continuous Action Spaces with Diffusion Trees for Reinforcement Learning
We propose a new approach for reinforcement learning in problems with continuous actions. Actions are sampled by means of a diffusion tree, which generates samples in the continuou...
Christian Vollmer, Erik Schaffernicht, Horst-Micha...
NN
2006
Springer
114views Neural Networks» more  NN 2006»
14 years 11 months ago
Modular learning models in forecasting natural phenomena
Modular model is a particular type of committee machine and is comprised of a set of specialized (local) models each of which is responsible for a particular region of the input s...
Dimitri P. Solomatine, Michael Baskara L. A. Siek
CONNECTION
2006
172views more  CONNECTION 2006»
14 years 11 months ago
Temporal sequence detection with spiking neurons: towards recognizing robot language instructions
We present an approach for recognition and clustering of spatio temporal patterns based on networks of spiking neurons with active dendrites and dynamic synapses. We introduce a n...
Christo Panchev, Stefan Wermter