We propose adaptive nonlinear auto-associative modeling (ANAM) based on Locally Linear Embedding algorithm (LLE) for learning intrinsic principal features of each concept separatel...
We introduce a new class of Reinforcement Learning algorithms designed to operate in perceptual spaces containing images. They work by classifying the percepts using a computer vi...
Wavelet neural networks (WNN) have recently attracted great interest, because of their advantages over radial basis function networks (RBFN) as they are universal approximators bu...
PSO is a population-based technique for optimization, which simulates the social behavior of the fish schooling or bird flocking. Two significant weaknesses of this method are: fir...
It has already been shown how Artificial Neural Networks (ANNs) can be incorporated into probabilistic models. In this paper we review some of the approaches which have been prop...