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NN
2008
Springer
14 years 9 months ago
Multilayer in-place learning networks for modeling functional layers in the laminar cortex
Currently, there is a lack of general-purpose in-place learning networks that model feature layers in the cortex. By "general-purpose" we mean a general yet adaptive hig...
Juyang Weng, Tianyu Luwang, Hong Lu, Xiangyang Xue
IAT
2005
IEEE
15 years 3 months ago
Self-Organizing Cognitive Agents and Reinforcement Learning in Multi-Agent Environment
This paper presents a self-organizing cognitive architecture, known as TD-FALCON, that learns to function through its interaction with the environment. TD-FALCON learns the value ...
Ah-Hwee Tan, Dan Xiao
ATAL
2005
Springer
15 years 3 months ago
Behavior transfer for value-function-based reinforcement learning
Temporal difference (TD) learning methods [22] have become popular reinforcement learning techniques in recent years. TD methods have had some experimental successes and have been...
Matthew E. Taylor, Peter Stone
NN
2000
Springer
192views Neural Networks» more  NN 2000»
14 years 9 months ago
A new algorithm for learning in piecewise-linear neural networks
Piecewise-linear (PWL) neural networks are widely known for their amenability to digital implementation. This paper presents a new algorithm for learning in PWL networks consistin...
Emad Gad, Amir F. Atiya, Samir I. Shaheen, Ayman E...
CORR
2010
Springer
103views Education» more  CORR 2010»
14 years 9 months ago
Asymptotic Learning Curve and Renormalizable Condition in Statistical Learning Theory
Bayes statistics and statistical physics have the common mathematical structure, where the log likelihood function corresponds to the random Hamiltonian. Recently, it was discovere...
Sumio Watanabe