Self-Learning Control of Finite Markov Chains

by A.S. Poznyak, Kaddour Najim, E. Gomez-Ramirez

Overview

Presents a number of new and potentially useful self-learning (adaptive) control algorithms and theoretical as well as practical results for both unconstrained and constrained finite Markov chains-efficiently processing new information by adjusting the control strategies directly or indirectly.

Product Details

ISBN-13:	9781351990721
Publisher:	CRC Press
Publication date:	10/03/2018
Series:	Automation and Control Engineering
Sold by:	Barnes & Noble
Format:	eBook
Pages:	314
File size:	6 MB

About the Author

Poznyak, A.S.; Najim, Kaddour; Gomez-Ramirez, E.

Table of Contents

Controlled Markov chains. Unconstrained Markov chains: Lagrange multipliers approach; penalty function approach; projection gradient method. Constrained Markov chains: Lagrange multipliers approach; penalty function approach; nonregular Markov chains; practical aspects.