This paper presents an agent-based approach to semantic exploration and knowledge discovery in large information spaces by means of capturing, visualizing and making usable implic...
Jasminko Novak, Michael Wurst, Monika Fleischmann,...
Using a combination of machine learning probabilistic tools, we have shown that some chemistry students fail to develop productive problem solving strategies through practice alon...
Ron Stevens, Amy Soller, Alessandra Giordani, Luca...
Due to the non-stationary environment, learning in multi-agent systems is a challenging problem. This paper first introduces a new gradient-based learning algorithm, augmenting th...
Which active learning methods can we expect to yield good performance in learning binary and multi-category logistic regression classifiers? Addressing this question is a natural ...
Solutions to complex tasks often require the cooperation of multiple robots, however, developing multi-robot policies can present many challenges. In this work, we introduce teach...