We give the first rigorous upper bounds on the error of temporal difference (td) algorithms for policy evaluation as a function of the amount of experience. These upper bounds pr...
Some of the most successful recent applications of reinforcement learning have used neural networks and the TD algorithm to learn evaluation functions. In this paper, we examine t...
—Failure recovery in IP networks is critical to high quality service provisioning. The main challenge is how to achieve fast recovery without introducing high complexity and reso...
Resiliency to link failures in optical networks is becoming increasingly important due to the increasing data rate in the fiber. Path protection schemes attempt to guarantee a bac...
Abstract—MPLS recovery mechanisms are increasing in popularity because they can guarantee fast restoration and high QoS assurance. Their main advantage is that their backup paths...