Results 251 to 260 of about 15,837 (289)

Using Semi-Markov Chains to Solve Semi-Markov Processes

Methodology and Computing in Applied Probability, 2020
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Wu, Bei, Maya, Brenda Ivette Garcia, Limnios, Nikolaos   +2 more
openaire   +3 more sources

SEMI-MARKOV DECISION PROCESSES

Probability in the Engineering and Informational Sciences, 2007
Considered are semi-Markov decision processes (SMDPs) with finite state and action spaces. We study two criteria: the expected average reward per unit time subject to a sample path constraint on the average cost per unit time and the expected time-average variability.
M. Baykal-Gürsoy, K. Gürsoy
openaire   +2 more sources

Regenerative generalized semi-markov processes

Communications in Statistics. Stochastic Models, 1987
The authors deal with a generalized semi-Markov process, which permits formal specification of some non-Markovian simulation models.
Haas, Peter J., Shedler, Gerald S.
openaire   +1 more source

Comparing Semi-Markov Processes

Mathematics of Operations Research, 1980
Sufficient conditions are found for two semi-Markov processes to be stochastically ordered, i.e., for which two new semi-Markov processes can be constructed on a common probability space so that the new processes individually have the same distributions as the original processes and every sample path of the first new process lies below the ...
openaire   +1 more source

Semi-Markov Processes

2001
Let Q(x,A,t), x ∈ E, A ∈ e,t ∈ IR+, be a semi-Markov kernel on (E,e) and let (J n ,S n )n∈N and (J n ,X n )n∈N be, respectively, the associated MRP and the (J-X)-process (see Section 2.2).
N. Limnios, G. Oprişan
openaire   +1 more source

Monotonicity in Generalized Semi-Markov Processes

Mathematics of Operations Research, 1992
We establish stochastic monotonicity of the event epoch sequences of generalized semi-Markov processes through the structure of the generalized semi-Markov schemes on which they are based. Our main condition states, roughly, that the occurrence of more events in the short run never leads to the activation of less events in the long run.
Glasserman, Paul, Yao, David D.
openaire   +2 more sources

Functions of Semi-Markov Processes

SIAM Journal on Applied Mathematics, 1971
A necessary and sufficient condition is presented under which a function of a semi-Markov process is again a semi-Markov process with transition probabilities which do not depend on the initial distribution of the original process. This result is a generalization of a known result for Markov processes.
openaire   +1 more source

Irregular semi-Markov processes

Ukrainian Mathematical Journal, 1989
See the review in Zbl 0688.60070.
openaire   +1 more source