Reward processes with nonlinear reward functions
Copyright policy )Reward processes with nonlinear reward functions
Based on a semi-Markov process J(t), t ≧ 0, a reward process Z(t), t ≧ 0, is introduced where it is assumed that the reward function, p(k, x) is nonlinear; if the reward function is linear, i.e. ρ (k, x) = kx, the reward process Z(t), t ≧ 0, becomes the classical one, which has been considered by many authors. An explicit formula for E(Z(t)) is given in terms of the moments of the sojourn time distribution at t, when the reward function is a polynomial.
- Shiraz University Iran (Islamic Republic of)
Markov renewal processes, semi-Markov processes, Applications of queueing theory (congestion, allocation, storage, traffic, etc.), Laplace transform, Renewal theory, semi-Markov processes, reward processes
Markov renewal processes, semi-Markov processes, Applications of queueing theory (congestion, allocation, storage, traffic, etc.), Laplace transform, Renewal theory, semi-Markov processes, reward processes
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