Self-Learning Control of Finite Markov Chains

Informationen zum Autor Poznyak! A.S.; Najim! Kaddour; Gomez-Ramirez! E. Klappentext Presents a number of fresh and helpful self-learning (adaptive) control algorithms and theoretical as well as practical results for both unconstrained and constrained finite Markov chains - processing fresh information by adjusting the control strategies directly or indirectly. Zusammenfassung 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. Inhaltsverzeichnis 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.

Product details

• Authors: E. Gomez-Ramirez, K. Najim, Kaddour Najim, Kaddour Gomez-Ramirez Najim, Najim Kaddour, A.s. Etc. Pozniak, A.s. Najim Pozniak, A.S. Poznyak, A.s. Najim Poznyak, Alexander S. Poznyak
• Publisher: Taylor & Francis Ltd.
• Languages: English
• Product format: Hardback
• Released: 03.01.2000
• EAN: 9780824794293
• ISBN: 978-0-8247-9429-3
• No. of pages: 316
• Series: Automation and Control Engineering; Automation and Control Engineering
• Subjects: Natural sciences, medicine, IT, technology > Mathematics > Miscellaneous; TECHNOLOGY & ENGINEERING / Automation, Stochastics, Automatic control engineering