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IJCAI
2007
13 years 9 months ago
Direct Code Access in Self-Organizing Neural Networks for Reinforcement Learning
TD-FALCON is a self-organizing neural network that incorporates Temporal Difference (TD) methods for reinforcement learning. Despite the advantages of fast and stable learning, TD...
Ah-Hwee Tan
ICPR
2000
IEEE
14 years 4 hour ago
Feature Learning for Recognition with Bayesian Networks
Many realistic visual recognition tasks are “open” in the sense that the number and nature of the categories to be learned are not initially known, and there is no closed set ...
Justus H. Piater, Roderic A. Grupen
IJSNET
2006
145views more  IJSNET 2006»
13 years 7 months ago
RL-MAC: a reinforcement learning based MAC protocol for wireless sensor networks
:This paper introduces RL-MAC, a novel adaptive MediaAccess Control (MAC) protocol for Wireless Sensor Networks (WSN) that employs a reinforcement learning framework. Existing sche...
Zhenzhen Liu, Itamar Elhanany
BMCBI
2008
138views more  BMCBI 2008»
13 years 7 months ago
Using neural networks and evolutionary information in decoy discrimination for protein tertiary structure prediction
Background: We present a novel method of protein fold decoy discrimination using machine learning, more specifically using neural networks. Here, decoy discrimination is represent...
Ching-Wai Tan, David T. Jones
GECCO
2005
Springer
149views Optimization» more  GECCO 2005»
14 years 1 months ago
There's more to a model than code: understanding and formalizing in silico modeling experience
Mapping biology into computation has both a domain specific aspect – biological theory – and a methodological aspect – model development. Computational modelers have implici...
Janet Wiles, Nicholas Geard, James Watson, Kai Wil...