This paper considers the problem of selecting the most informative experiments x to get measurements y for learning a regression model y = f(x). We propose a novel and simple conc...
We consider reinforcement learning in systems with unknown dynamics. Algorithms such as E3 (Kearns and Singh, 2002) learn near-optimal policies by using "exploration policies...
Two notions of optimality have been explored in previous work on hierarchical reinforcement learning (HRL): hierarchical optimality, or the optimal policy in the space defined by ...
A large number of industrial concurrent programs are being designed based on a model which combines threads with event-based communication. These programs consist of several threa...
Vineet Kahlon, Nishant Sinha, Erik Kruus, Yun Zhan...
We combine a pen and pressure-sensitive tablet input device, and a sketch-based user initialization process, with a general subdivisioncurve Snake to create an intuitive, fast, ac...