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...
—Peer-assisted Video-on-Demand (VoD) systems have not only received substantial recent research attention, but also been implemented and deployed with success in large-scale real...
We consider the problem of efficiently learning optimal control policies and value functions over large state spaces in an online setting in which estimates must be available afte...
In this paper, we consider Markov Decision Processes (MDPs) with error states. Error states are those states entering which is undesirable or dangerous. We define the risk with re...
We develop algorithms for finding minimum energy disjoint paths in an all-wireless network, for both the node and linkdisjoint cases. Our major results include a novel polynomial...