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» Towards a novel networked learning environment
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AUSAI
1999
Springer
15 years 6 months ago
Q-Learning in Continuous State and Action Spaces
Abstract. Q-learning can be used to learn a control policy that maximises a scalar reward through interaction with the environment. Qlearning is commonly applied to problems with d...
Chris Gaskett, David Wettergreen, Alexander Zelins...
109
Voted
IJCNN
2008
IEEE
15 years 8 months ago
A neural wake-sleep learning architecture for associating robotic facial emotions
—A novel wake-sleep learning architecture for processing a robot’s facial expressions is introduced. According to neuroscience evidence, associative learning of emotional respo...
Chi-Yung Yau, Kevin Burn, Stefan Wermter
100
Voted
IVC
2000
104views more  IVC 2000»
15 years 1 months ago
Learning spatio-temporal patterns for predicting object behaviour
Rule-based systems employed to model complex object behaviours, do not necessarily provide a realistic portrayal of true behaviour. To capture the real characteristics in a specif...
Neil Sumpter, Andrew J. Bulpitt
CEC
2007
IEEE
15 years 8 months ago
Evolving neuromodulatory topologies for reinforcement learning-like problems
— Environments with varying reward contingencies constitute a challenge to many living creatures. In such conditions, animals capable of adaptation and learning derive an advanta...
Andrea Soltoggio, Peter Dürr, Claudio Mattius...
HIS
2008
15 years 3 months ago
A Sequential Learning Resource Allocation Network for Image Processing Applications
Online adaptation is a key requirement for image processing applications when used in dynamic environments. In contrast to batch learning, where retraining is required each time a...
Stefan Wildermann, Jürgen Teich