— Due to the abundant application background, the optimization of maintenance problem has been extensively studied in the past decades. Besides the well-known difficulty of larg...
It has recently been shown how to construct online, non-amortised approximate pattern matching algorithms for a class of problems whose distance functions can be classified as be...
Given a set of machines and a set of Web applications with dynamically changing demands, an online application placement controller decides how many instances to run for each appl...
Chunqiang Tang, Malgorzata Steinder, Mike Spreitze...
Markov decision processes (MDPs) are an established framework for solving sequential decision-making problems under uncertainty. In this work, we propose a new method for batchmod...
We propose a new approach to reinforcement learning which combines least squares function approximation with policy iteration. Our method is model-free and completely off policy. ...