this paper presents a discrete-time single-server finite buffer n threshold policy queue with renewal input and discretemarkovian service process. the server terminates service whenever the system becomes empty, and recommencesservice as soon as the number of waiting customers in the queue is n. we obtain the system-length distributionsat pre-arrival and arbitrary epochs using the supplementary...

.................................................................................................................... 2 Preface ....................................................................................................................... 3 Acknowledgements................................................................................................... 4 Chapter 1: Introduction .........

We develop a systematic description of Weyl and Fano operators on a lattice phase space. Introducing the so-called ghost variable even on an odd lattice, odd and even lattices can be treated in a symmetric way. The Wigner function is defined using these operators on the quantum phase space, which can be interpreted as a spin phase space. If we extend the space with a dichotomic variable, a posi...

We describe a Markov process which models the sequential allocation for two adjacent tables coexisting in memory by growing towards each other. The tables are expected to ll at the same rate; random deletions and insertions are allowed.

In this paper we present an adaptive algorithm to estimate the transient blocking probability of a communication system, described by a Markov process, during a finite time interval starting from a given state. The method uses importance sampling for variance reduction and adjusts the parameters of the twisted distribution based on earlier samples. The method can be effectively applied to a dec...

We describe a Markov process which models the sequential allocation for two adjacent tables coexisting in memory by growing towards each other. The tables are expected to ll at the same rate; random deletions and insertions are allowed.

The Partially Observable Markov Decision Process (POMDP) framework has proven useful in planning domains where agents must balance actions that provide knowledge and actions that provide reward. Unfortunately, most POMDPs are complex structures with a large number of parameters. In many real-world problems, both the structure and the parameters are difficult to specify from domain knowledge alo...