This paper presents a cognitive agent model capable of showing situations where self-generated actions are attributed to other agents, as, for example, for patients suffering from ...
Abstract. In this study we propose a novel model for the representation of biological networks and provide algorithms for learning model parameters from experimental data. Our appr...
When search is against structured documents, it is beneficial to extract information from user queries in a format that is consistent with the backend data structure. As one step...
With our interest to improve our education in computer science, an understanding of how students learn about CS concepts, how different concepts are understood, as well as the con...
Mordechai Ben-Ari, Anders Berglund, Shirley Booth,...
We use unsupervised probabilistic machine learning ideas to try to explain the kinds of learning observed in real neurons, the goal being to connect abstract principles of self-or...