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ESANN
2008
15 years 8 months ago
Learning to play Tetris applying reinforcement learning methods
In this paper the application of reinforcement learning to Tetris is investigated, particulary the idea of temporal difference learning is applied to estimate the state value funct...
Alexander Groß, Jan Friedland, Friedhelm Sch...
IJCNN
2006
IEEE
16 years 21 days ago
A Very Small Chaotic Neural Net
— Previously we have shown that chaos can arise in networks of physically realistic neurons [1], [2]. Those networks contain a moderate to large number of units connected in a sp...
Carlos Lourenco
IJCNN
2006
IEEE
16 years 21 days ago
Anti-swing control for overhead crane with neural compensation
— This paper considers the problem of PD control of overhead crane in the presence of uncertainty associated with crane dynamics. By using radial basis function neural networks, ...
Rigoberto Toxqui Toxqui, Wen Yu, Xiaoou Li
NN
2000
Springer
167views Neural Networks» more  NN 2000»
15 years 6 months ago
Blind signal processing by the adaptive activation function neurons
The aim of this paper is to study an Information Theory based learning theory for neural units endowed with adaptive activation functions. The learning theory has the target to fo...
Simone Fiori
FPGA
2009
ACM
201views FPGA» more  FPGA 2009»
16 years 1 months ago
A high-performance FPGA architecture for restricted boltzmann machines
Despite the popularity and success of neural networks in research, the number of resulting commercial or industrial applications have been limited. A primary cause of this lack of...
Daniel L. Ly, Paul Chow