In a variety of applications, kernel machines such as Support Vector Machines (SVMs) have been used with great success often delivering stateof-the-art results. Using the kernel t...
Approximate Linear Programming (ALP) is a reinforcement learning technique with nice theoretical properties, but it often performs poorly in practice. We identify some reasons for...
Virtually all methods of learning dynamic systems from data start from the same basic assumption: that the learning algorithm will be provided with a sequence, or trajectory, of d...
We present the implementation of several programming languages with support for multi-dimensional separation of concerns (MDSOC) on top of a common delegation-based substrate, whi...
In spite of its growing popularity, due to a huge technical evolution in the last years and to the fact that new generations are more literate in games than in books, game-based te...