Abstract a paradigm of modern Machine Learning (ML) which uses rewards and punishments to guide the learning process. One of the central ideas of RL is learning by “direct-online...
— This paper is interested in reward maximization of periodic real-time tasks under a given energy constraint, where the reward received depends on how much computation a task ru...
Many peer-assisted content-distribution systems reward a peer based on the amount of data that this peer serves to others. However, validating that a peer did so is, to our knowled...
Michael K. Reiter, Vyas Sekar, Chad Spensky, Zheng...
The imprecise computation(IC) model is a general scheduling framework, capable of expressing the precision vs. timeliness trade-off involved in many current real-time applications...
Online reputation mechanisms need honest feedback to function effectively. Self interested agents report the truth only when explicit rewards offset the cost of reporting and th...