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 ...
In this paper we analyze the problem of estimating a function from different noisy data sets collected by spatially distributed sensors and subject to unknown temporal shifts. We p...
In this note, the novel representation is proposed for a linear periodic continuous-time system with T-periodic real-valued coefficients. We prove that a T-periodic real-valued fac...
Traffic burstiness has a significant impact on network performance. Burstiness can cause buffer overflows and packet drops and is particularly problematic in the context of small-b...
In this paper, we study the reliable decentralized supervisory control of discrete event systems (DESs) under the general architecture, in which the decision for controllable event...