— We propose a learning algorithm for estimating the 3-D orientation of objects. Orientation learning is a difficult problem because the space of orientations is non-Euclidean, ...
Shaping functions can be used in multi-task reinforcement learning (RL) to incorporate knowledge from previously experienced tasks to speed up learning on a new task. So far, rese...
We present a subspace learning method, called Local Discriminant Embedding with Tensor representation (LDET), that addresses simultaneously the generalization and data representat...
Predictive state representations (PSRs) are models that represent the state of a dynamical system as a set of predictions about future events. The existing work with PSRs focuses ...
Britton Wolfe, Michael R. James, Satinder P. Singh
The cognitive models of information representation are fundamental research areas in cognitive informatics, which attempts to reveal the mechanisms and potential of the brain in l...