Markov Decision Processes and Stochastic Positional Games: Optimal Control on Complex Networks

by Dmitrii Lozovanu, Stefan Wolfgang Pickl

Overview

This book presents recent findings and results concerning the solutions of especially finite state-space Markov decision problems and determining Nash equilibria for related stochastic games with average and total expected discounted reward payoffs. In addition, it focuses on a new class of stochastic games: stochastic positional games that extend and generalize the classic deterministic positional games. It presents new algorithmic results on the suitable implementation of quasi-monotonic programming techniques. Moreover, the book presents applications of positional games within a class of multi-objective discrete control problems and hierarchical control problems on networks.

Given its scope, the book will benefit all researchers and graduate students who are interested in Markov theory, control theory, optimization and games.

Product Details

ISBN-13:	9783031401800
Publisher:	Springer-Verlag New York, LLC
Publication date:	01/12/2024
Series:	International Series in Operations Research & Management Science , #349
Sold by:	Barnes & Noble
Format:	eBook
File size:	41 MB
Note:	This product may take a few minutes to download.

About the Author

Prof. Dmitrii Lozovanu is head of the department of Applied Mathematics at the Faculty of Mathematics and Computer Science, Moldova State University, Chisinau, Moldova. His main research interests are in discrete optimization, game theory, optimal control and stochastic decision-making processes.

​Prof. Stefan Pickl is a Professor of Operations Research at Bundeswehr University Munich, Germany. He studied mathematics, electrical engineering, and philosophy at the TU Darmstadt, Germany and EPFL Lausanne, Switzerland. He is also associated with the Centre for the Advanced Study of Algorithms (CASA), USA and Center for Network Innovation and Experimentation (CENETIX), USA.

Table of Contents

Discrete Markov Processes and Numerical Algorithms for Markov Chains.- Markov Decision Processes and Stochastic Control Problems on Networks.- Stochastic Games and Positional Games on Networks