We consider the problem of multi-task reinforcement learning where the learner is provided with a set of tasks, for which only a small number of samples can be generated for any g...
This article proposes an algorithm to automatically learn useful transformations of data to improve accuracy in supervised classification tasks. These transformations take the for...
tion Learning about Temporally Abstract Actions Richard S. Sutton Department of Computer Science University of Massachusetts Amherst, MA 01003-4610 rich@cs.umass.edu Doina Precup D...
Richard S. Sutton, Doina Precup, Satinder P. Singh
Developing automated agents that intelligently perform complex real world tasks is time consuming and expensive. The most expensive part of developing these intelligent task perfo...
Existing ML-like languages guarantee type-safety, ensuring memty and protecting the invariants of abstract types, but only within single executions of single programs. Distributed...
John Billings, Peter Sewell, Mark R. Shinwell, Rok...