Business analytics aims to enable organizations to make quicker, better, and more
intelligent decisions with the aim to create business value. To date, the major focus in the …

Heuristically, a discrete-time stochastic process has the Markov property if the past and
future are independent given the present. In this introductory chapter, we give the formal …

Classical applications of control engineering and information and communication
technology (ICT) in production and logistics are often done in a rigid, centralized and …

The Poisson equation has wide applications in many areas of science and engineering.
Although there are some quantum algorithms that can efficiently solve the Poisson equation …

An up-to-date account of the interplay between optimization and machine learning,
accessible to students and researchers in both communities. The interplay between …

Markov Chains and Stochastic Stability is part of the Communications and Control
Engineering Series (CCES) edited by Professors BW Dickinson, ED Sontag, M. Thoma, A …

In networked control systems (NCS), agents participating in a network share their data with
others to work together. When agents share their data, they can naturally expose the NCS to …

A widely recognized shortcoming of model predictive control (MPC) is that it can usually only
be used in applications with slow dynamics, where the sample time is measured in seconds …

We present four new reinforcement learning algorithms based on actor-critic and natural-
gradient ideas, and provide their convergence proofs. Actor-critic rein-forcement learning …

Provides a modern mathematical approach to the design of communication networks for
graduate students, blending control, optimization, and stochastic network theories. A broad …