Creating autonomous robots that can actively explore the environment, acquire knowledge
and learn skills continuously is the ultimate achievement envisioned in cognitive and …

This paper deals with the possibility of predicting student's grades based on their usage of
Learning Management System (LMS) Moodle. It is important to know what materials would …

The impressive results of applying deep neural networks in tasks such as object recognition,
language translation, and solving digital games are largely attributed to the availability of …

What is a proper representation for objects in manipulation? What would human try to
perceive when manipulating a new object in a new environment? In fact, instead of focusing …

In this work, a complete solution is provided for detecting and identifying cylindrical shapes,
which are commonly found in household and industrial environments, using consumer …

This paper deals with the idea of calculating probabilities and percentages with Petri nets.
Uncertainty can be expressed with Petri nets as one place with multiple output transitions. In …

In order to effectively handle multiple tasks that are not predefined, a robotic agent needs to
automatically map its high-dimensional sensory inputs into useful features. As a solution …

In robotics, affordances are used as a theoretical framework for guiding a robot's interaction
with the objects within its environment. In particular, affordances are formalized in order to …

Recent advances in deep learning, in particular in convolutional neural networks (CNNs),
have been widely used in robotics for object classification and action recognition, among …

One of the main advantages of building robots with size and motor capabilities close to
those of humans, such as iCub, lies in the fact that they can potentially take advantage of a …