— We consider a distributed system modeled as a possibly large network of automata. Planning in this system consists in selecting and organizing actions in order to reach a goal ...
We introduce a method to deal with the problem of learning from imbalanced data sets, where examples of one class significantly outnumber examples of other classes. Our method sel...
DT Tutor uses a decision-theoretic approach to select tutorial actions for coached problem solving that are optimal given the tutor's beliefs and objectives. It employs a mode...
An image representation framework based on structured sparse model selection is introduced in this work. The corresponding modeling dictionary is comprised of a family of learned ...
— This paper presents a case study of learning to select behavioral primitives and generate subgoals from observation and practice. Our approach uses local features to generalize...
Darrin C. Bentivegna, Christopher G. Atkeson, Gord...