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...
We argue that while work to optimize the accessibility of the World Wide Web through the publication and dissemination of a range of guidelines is of great importance, there is al...
David Sloan, Andy Heath, Fraser Hamilton, Brian Ke...
Abstract. The Reliable Server Pooling (RSerPool) protocol suite currently under standardization by the IETF is designed to build systems providing highly available services by prov...
Thomas Dreibholz, Erwin P. Rathgeb, Michael Tü...
Distributed partially observable Markov decision problems (POMDPs) have emerged as a popular decision-theoretic approach for planning for multiagent teams, where it is imperative f...
Resource limited DRE (Distributed Real-time Embedded) systems can benefit greatly from dynamic adaptation of system parameters. We propose a novel approach that employs iterative t...
Minyoung Kim, Mark-Oliver Stehr, Carolyn L. Talcot...