Learning from data streams is a research area of increasing importance. Nowadays, several stream learning algorithms have been developed. Most of them learn decision models that c...
Several published reports show that instancebased learning algorithms yield high classification accuracies and have low storage requirements during supervised learning application...
Abstract. Over the last decade, first-order constraints have been efficiently used in the artificial intelligence world to model many kinds of complex problems such as: scheduling,...
A key problem in reinforcement learning is finding a good balance between the need to explore the environment and the need to gain rewards by exploiting existing knowledge. Much ...
Model trees—decision trees with linear models at the leaf nodes—have recently emerged as an accurate method for numeric prediction that produces understandable models. However,...