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» Introduction to artificial neural networks
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AUSAI
1999
Springer
15 years 2 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...
FLAIRS
2008
15 years 7 days ago
Fuzzy Clustering Paradigm and the Shape-Based Image Retrieval
This paper presents a strategy for shape-based image retrieval in which moment invariants form a feature vector to describe the shape of an object. Fuzzy k-means clustering is use...
Nan Xing, Imran Shafiq Ahmad
CEC
2008
IEEE
14 years 12 months ago
Learning defect classifiers for visual inspection images by neuro-evolution using weakly labelled training data
This article presents results from experiments where a detector for defects in visual inspection images was learned from scratch by EANT2, a method for evolutionary reinforcement l...
Nils T. Siebel, Gerald Sommer
ISMB
1994
14 years 11 months ago
DNA Sequence Analysis Using Hierarchical ART-based Classification Network
Adaptive resonance theory (ART)describes a class of artificial neural networkarchitectures that act as classification tools whichself-organize, workin realtime, and require no ret...
Cathie LeBlanc, Charles R. Katholi, Thomas R. Unna...
SIGDOC
2003
ACM
15 years 3 months ago
Using AI techniques to aid hypermedia design
Artificial intelligence techniques have found a number of applications in hypermedia, mostly in two specific areas, user interface, particularly adaptive ones and information sear...
Elena I. Gaura, Robert M. Newman