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Calculating the variance in Markov-processes with random reward.

Francisco Benito (1982)

Trabajos de Estadística e Investigación Operativa

In this article we present a generalization of Markov Decision Processes with discreet time where the immediate rewards in every period are not deterministic but random, with the two first moments of the distribution given.Formulas are developed to calculate the expected value and the variance of the reward of the process, formulas which generalize and partially correct other results. We make some observations about the distribution of rewards for processes with limited or unlimited horizon and...

Calculation of Reliability Characteristics for Regenerative Models

Kalashnikov, Vladimir (1996)

Serdica Mathematical Journal

If a regenerative process is represented as semi-regenerative, we derive formulae enabling us to calculate basic characteristics associated with the first occurrence time starting from corresponding characteristics for the semi-regenerative process. Recursive equations, integral equations, and Monte-Carlo algorithms are proposed for practical solving of the problem.

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