End-user interactive machine learning is a promising tool for enhancing human productivity and capabilities with large unstructured data sets. Recent work has shown that we can cr...
Saleema Amershi, James Fogarty, Ashish Kapoor, Des...
Agent architectures have to cope with a number of internal properties (concerns), such as autonomy, learning, and mobility. As the agent complexity increases, these agent propertie...
Agent technology is a good approach for solving a number of problems concerned with personalized learning. In personal learning contexts individual students are given an environme...
Ali M. Aseere, Enrico H. Gerding, David E. Millard
Efficient Learning Equilibrium (ELE) is a natural solution concept for multi-agent encounters with incomplete information. It requires the learning algorithms themselves to be in ...
We introduce the notion of restricted Bayes optimal classifiers. These classifiers attempt to combine the flexibility of the generative approach to classification with the high ac...