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The development of robotic cognition and the advancement of understanding of human cognition form two of the current greatest challenges in robotics and neuroscience, respectively. The RobotCub project aims to develop an embodied robotic child (iCub) with ...
The capability to learn from experience is a key property for autonomous cognitive systems working in realistic settings. To this end, this paper presents an SVM-based algorithm, capable of learning model representations incrementally while keeping under c ...
A large body of work has been reported in the last 5 years on the development of lead-free piezoceramics in the quest to replace lead–zirconate–titanate (PZT) as the main material for electromechanical devices such as actuators, sensors, and transducers. I ...
Exploratory activities seem to be intrinsicallyrewarding for children and crucial for their cognitive development. Can a machine be endowed with such an intrinsic motivation system? This is the question we study in this paper, presenting a number of comput ...
This paper presents a new approach for monitoring and estimating device reliability of nanometer-scale devices prior to fabrication. A four-layer architecture exhibiting a large immunity to permanent as well as random failures is used. A complete tool for ...
Current available risk analysis techniques are well adapted to industry needs since they were developed for its purpose. All hazards present in industry are also met in research/academia, although quantities of some hazardous substances are smaller. Still, ...
This paper discusses a time-dependent classification approach for single trial recognition of spatial covert visual attention for Brain–Computer Interface. Covert visual attention is a natural and intuitive mental task that does not require any external st ...
Autism covers a wide spectrum of disorders for which there are many views, hypotheses and theories. Here we propose a unifying theory of autism, the Intense World Theory. The proposed neuropathology is hyper-functioning of local neural microcircuits, best ...
Computational models have played a central role in the debate over language learnability. This article discusses how they have been used in different stances, from generative views to more recently introduced explanatory frameworks based on embodiment, cog ...
The capability to learn from experience is a key property for autonomous cognitive systems working in realistic settings. To this end, this paper presents an SVM- -based algorithm, capable of learning model representations incrementally while keeping under ...