1. Definition
- let $N(t)$ be a renewal process
- Let $R_n$ = reward earned at $n$-th renewal
- Assume $R_n$ are i.i.d, but can depend on $X_n$ (length of the $n$-th cycle)
Then $R(t) = \sum^{N(t)}_{n=1} R_n$ is a renewal reward process.
Intuitive explanation: $R(t)$ = cumulative reward earned up to time t
2. Renewal Reward Theorem
Proposition 7.3
- $lim_{t \to \infty} \frac{R(t)}{t} = \frac{E[R_n]}{E[X_n]}$
- $lim_{t \to \infty} \frac{E[R(t)]}{t} = \frac{E[R_n]}{E[X_n]} $
Provided $E[R_n] < \infty, E[X_n] < \infty$
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