The general stochastic optimal control (SOC) problem in robotics scenarios is often too complex to be solved exactly and in near real time. A classical approximate solution is to ...
For supervised learning, feature selection algorithms attempt to maximise a given function of predictive accuracy. This function usually considers the ability of feature vectors t...
Abstract. We compare three systems for the task of synthesising functional recursive programs, namely Adate, an approach through evolutionary computation, the classification learn...
Martin Hofmann 0008, Andreas Hirschberger, Emanuel...
A new method for optimizing complex functions and systems is described that employs Learnable Evolution Model (LEM), a form of non-Darwinian evolutionary computation guided by mac...
Ryszard S. Michalski, Janusz Wojtusiak, Kenneth A....
We consider the problem of recognizing human actions from still images. We propose a novel approach that treats the pose of the person in the image as latent variables that will h...