Research on modelling affect and on interfaces adaptation based on affective factors has matured considerably over the past several years, so that designers of educational product...
In recent years analysis of complexity of learning Gaussian mixture models from sampled data has received significant attention in computational machine learning and theory commun...
Bayesian Networks are today used in various fields and domains due to their inherent ability to deal with uncertainty. Learning Bayesian Networks, however is an NP-Hard task [7]....
A framework for task assignment in heterogeneous computing systems is presented in this work. The framework is based on a learning automata model. The proposed model can be used f...
Many complex, real world phenomena are difficult to study directly using controlled experiments. Instead, the use of computer simulations has become commonplace as a feasible alte...