DETERMINATION OF RECURRENT ALGORITHMS AND OPTIMAL STRATEGIES FOR CONTROLLED MARKOV CHAINS
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Abstract
Article controlled Markov chains for recurrent algorithms and optimal strategies determination to the issues dedicated . Managed random processes , especially industrial of enterprises work activity planning such as practical in the fields application seeing The states of the system are Markov random . process with modeled , each one in case various to strategies suitable to pass probabilities and income analysis The goal is to one in step maximum average income optimal strategy that provides find . Recurring algorithms using expected income and optimal strategies consecutively is considered . From this except , asymptotic formulas optimal strategies using determination methods Example as two stately and two strategic Markov process for calculations and tables presented is done , this optimal strategies through is determined . Article practical and theoretical in terms of controlled Markov processes study for important source is considered .
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References
1.Bellman, R. (1957). Dynamic Programming. Princeton University Press.
2.Howard, R. A. (1960). Dynamic Programming and Markov Processes. MIT Press.
3.Bertsekas, D. P. (1995). Dynamic Programming and Optimal Control. Athena Scientific.
4.Filar, J., & Vrieze, K. (1997). Competitive Markov Decision Processes. Springer.
5.Altman, E. (1999). Constrained Markov Decision Processes . Chapman and Hall/CRC.
6.Ikramov , A., & Shirinov , T. (2015). " Managed random of processes industry in systems " Uzbekistan " mathematics Journal , 3(2), 45–52.
7.Markov, A. A. (1906). " Distribution law more numbers on magnitudes , drug dependent druga . " News Physico-mathematical society at Kazan universitete , 15(4), 135–156.