Many important applications in global optimization, algebra, probability and statistics,
applied mathematics, control theory, financial mathematics, inverse problems, etc. can be …

The theory of Markov decision processes focuses on controlled Markov chains in discrete
time. The authors establish the theory for general state and action spaces and at the same …

Eugene A. Feinberg Adam Shwartz This volume deals with the theory of Markov Decision
Processes (MDPs) and their applications. Each chapter was written by a leading expert in …

Power grids, flexible manufacturing, cellular communications: interconnectedness has
consequences. This remarkable book gives the tools and philosophy you need to build …

In Chap. 2, we formally introduce the concepts associated to a continuous time MDP.
Namely, the basic model of continuous-time MDPs and the concept of a Markov policy are …

We consider the batch (off-line) policy learning problem in the infinite horizon Markov
Decision Process. Motivated by mobile health applications, we focus on learning a policy …

We consider the class of nonlinear optimal control problems (OCPs) with polynomial data,
ie, the differential equation, state and control constraints, and cost are all described by …

This book is about discrete-time, time-homogeneous, Markov chains (Mes) and their ergodic
behavior. To this end, most of the material is in fact about stable Mes, by which we mean …

Many owners of growing privately held firms make operational and financial decisions in an
effort to maximize the expected present value of the proceeds from an initial public offering …

Approximate value iteration (AVI) is a method for solving large Markov decision problems by
approximating the optimal value function with a sequence of value function representations …