Markov Rewards Processes with Impulse Rewards and Absorbing States
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We study the expected accumulated reward for a discrete-time Markov reward model with absorbing states. The rewards are impulse rewards, where a reward ρ_ij is accumulated when transitioning from state i to state j. We derive an explicit, single-letter expression for the expected accumulated reward as a function of the number of time steps n and include in our analysis the limit in which n →∞.
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