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Alexander S. Poznyak, Self-Learning Control of Finite Markov Chains

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Written for upper-level undergraduates, graduate students, and professionals in the engineering, mathematics, and statistics fields, this book presents the fundamental mathematical concepts of self-learning control of constrained and unconstrained finite Markov chains. MATLAB M-files that illustrate the concepts in the text, are presented in the appendix. These files require the Optimization Toolbox.

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	Mathematics Self-Learning Control of Finite Markov Chains
	Science/Engineering From Markov Chains to Non-Equilibrium Particle Systems, Second Edition (Reupload) From Markov Chains to Non-Equilibrium Particle Systems, Second Edition Publisher: World Scientific Publishing Company \| ISBN: 9812388117 \| edition 2004 \| PDF \| 612 pages \| 21,9 mbThis book is representative of the work of Chinese probabili ...
	Economics/Finances Markov Chains and Stochastic Stability (Communications and Control Engineering): Sean P. Meyn, Richard L. Tweedie Markov Chains and Stochastic Stability (Communications and Control Engineering): Sean P. Meyn, Richard L. Tweedie Springer \| ISBN: 3540198326 \| 1996-03-19 \| PDF (OCR) \| 550 pages \| 5.54 Mb Markov Chains and Stochastic Stability is part of ...
	Science/Engineering Finite Markov chains, Undergraduate Texts in Mathematics Finite Markov chains, Undergraduate Texts in Mathematicsby: John G. Kemeny, James Laurie Snell Publisher: Springer \| 244 pages \| 1983 -12 -5 \| English \| ISBN: 0387901922 \| PDF \| 9.11 MBPreview The basic concepts of Markov chains were introd ...
	Programming Alexander S. Poznyak, ?Self-Learning Control of Finite Markov Chains? (Reupload) Alexander S. Poznyak, ?Self-Learning Control of Finite Markov Chains?ISBN: 082479429X \| Publisher: Marcel Dekker \| Publication Date: 2000-01-03 \| Number Of Pages: 314 \| djvu \| 2 mbSummary:Written for upper-level undergraduates, graduate st ...
	Science/Engineering Self-Learning Control of Finite Markov Chains (Control Engineering (Marcel Dekker), 4.) 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 a ...

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