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Optimization of piecewise-deterministic Markov models

Published online by Cambridge University Press:  01 July 2016

M. H. A. Davis
M. H. A. Davis*
Affiliation:
Imperial College, London
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Extract

Piecewise-deterministic (PD) Markov processes consist of a mixture of deterministic motion and random jumps, the jumps occurring ‘spontanteously’ in a Poisson-like fashion and also ‘surely’ when the process hits certain boundaries. They form a flexible class of stochastic models, including as special cases almost all the non-diffusion models of applied probability. The construction of these processes will be outlined and precise characterization of the extended generator given.

Information

Type
Applied Probability in Biology and Engineering. An ORSA/TIMS Special Interest Meeting
Information
Advances in Applied Probability , Volume 16 , Issue 1 , March 1984 , pp. 14
Copyright
Copyright © Applied Probability Trust 1984 

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References

Vinter, R. B. and Lewis, R. M. (1978) A necessary and sufficient condition for optimality of dynamic programming type, making no a priori assumptions on the controls. SIAM J. Control and Optimization 16, 571–583.CrossRefGoogle Scholar