Abstract— Q-learning is a technique used to compute an optimal policy for a controlled Markov chain based on observations of the system controlled using a non-optimal policy. It ...
This paper addresses the issue of how to meet the strict timing constraints of (soft) real-time virtualized applications while the Virtual Machine (VM) hosting them is undergoing a...
We focus on the combinatorial analysis of physical mapping with repeated probes. We present computational complexity results, and we describe and analyze an algorithmic strategy. W...
Abstract. Due to its prominence in artificial intelligence and theoretical computer science, the propositional satisfiability problem (SAT) has received considerable attention in...
In machine learning theory, problem classes are distinguished because of di erences in complexity. In 6 , a stochastic model of learning from examples was introduced. This PAClear...