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There are $n$ independent Bernoulli random variables $I_{k}$ with parameters $p_{k}$ that are observed sequentially. We consider a generalization of the Last-Success-Problem considering $w_{k}$ positive payments if the player successfully predicts that the last "1" occurs in the variable $I_{k}$. We establish the optimal strategy and the expected profit in similar terms to the Odds-Theorem. The proof provided here is an alternative proof to the one Bruss provides in his Odds-Theorem (case $w_{i}=1$) that is even simpler and more elementary than his proof., Comment: 8

There are $n$ independent Bernoulli random variables with parameters $p_i$ that are observed sequentially. Two players, A and B, act in turns starting with player A. Each player has the possibility on his turn, when $I_k=1$, to choose whether to continue with his turn or to pass his turn on to his opponent for observation of the variable $I_{k+1}$. If $I_k=0$, the player must necessarily to continue with his turn. After observing the last variable, the player whose turn it is wins if $I_n=1$, and loses otherwise. We determine the optimal strategy for the player whose turn it is and establish the necessary and sufficient condition for player A to have a greater probability of winning than player B. We find that, in the case of $n$ Bernoulli random variables with parameters $1/n$, the probability of player A winning is decreasing with $n$ towards its limit $\frac{1}{2} - \frac{1}{2\,e^2}=0.4323323...$. We also study the game when the parameters are the results of uniform random variables, $\mathbf{U}[0,1]$