Markov Chains For Programmers

 
Markov Chains For Programmers
Free Download Markov Chains For Programmers
English | 2022 | ISBN: n/a | 68 Pages | PDF | 2.5 MB
"Markov Chains for programmers" is devoted to programmers at any level wanting to understand more about the underpinnings of Markov Chains (MC) and basic solution methods.


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Markov Processes Volume I

 
Markov Processes Volume I
Free Download Markov Processes: Volume I by E. B. Dynkin
English | PDF | 1965 | 377 Pages | ISBN : 3662000334 | 29 MB
The modem theory of Markov processes has its origins in the studies of A. A. MARKOV (1906-1907) on sequences of experiments "connected in a chain" and in the attempts to describe mathematically the physical phenomenon known as Brownian motion (L. BACHELlER 1900, A. EIN STEIN 1905). The first correct mathematical construction of a Markov process with continuous trajectories was given by N. WIENER in 1923. (This process is often called the Wiener process.) The general theory of Markov processes was developed in the 1930's and 1940's by A. N. KOL MOGOROV, W. FELLER, W. DOEBLlN, P. LEVY, J. L. DOOB, and others. During the past ten years the theory of Markov processes has entered a new period of intensive development. The methods of the theory of semigroups of linear operators made possible further progress in the classification of Markov processes by their infinitesimal characteristics. The broad classes of Markov processes with continuous trajectories be came the main object of study.


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Markov Chains With Stationary Transition Probabilities

 
Markov Chains With Stationary Transition Probabilities
Free Download Markov Chains: With Stationary Transition Probabilities by Kai Lai Chung
English | PDF | 1967 | 312 Pages | ISBN : 3540038221 | 23.3 MB
In this revised edition I have added some new material as well as making corrections and improvements. In Part I the additions (in §§ 9, 10, 11) are a few results closely related to the original text and illustrative of the method of taboos. In Part II the major additions have to do with the boundary theory; these include "fine topology" in § 11, "Martin boundary" and "entrance law" in § 19. The old Addenda have been expanded into the new § 12, some of the developments there being also germane to the boundary theory. It is hoped that these efforts have now brought the reader right up to the edge of the boundary. A number of selected items have been inserted in the Bibliography as a further guide to the latest literature on the above-mentioned and other topics.


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Markov Decision Processes Discrete Stochastic Dynamic Programming

 
Markov Decision Processes Discrete Stochastic Dynamic Programming
Free Download Markov Decision Processes: Discrete Stochastic Dynamic Programming by Martin L. Puterman
English | PDF | 1994 | 665 Pages | ISBN : 0471619779 | 27.35 MB
The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists.


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