Dynamic Risk Control in Multidimensional Markov Models
The authors consider a typical model used in many fields of applied mathematics regarding selection of optimal decisions in stochastic systems. The multidimensional death process controlled on an interval of random length, which is analyzed in the paper, can be used to describe phenomena that appear in economical, biological, medical, engineering, and other applications. Several approaches are proposed to determine the optimality criteria, the properties of corresponding risk function are investigated, and a computing algorithm is developed for construction of optimal stationary strategies.
Keywordsoptimal stationary strategies controlled processes Markov decision-making processes risk function birth-death processes iterative algorithms
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