Smith is in jail and has 1 dollar; he can get out on bail if he has 8 dollars. A guard agrees to make a series of bets with him. If Smith bets A dollars, he wins A dollars with probability .4 and loses A dollars with probability .6. Find the probability that he wins 8 dollars before losing all of his money if
The Markov chain (Xn, n = 0, 1, . . .) representing the evolution of Smith’s money
Let \(\varphi(i)\) be the probability that the chain reaches state 8 before reaching state 0, starting from state i. In other words, if \(S_j\) is the first \(n \geq 0\) such that \(X_n = j\),
\[\varphi(i) = P_i(S_8 < S_0) = P(S_8 < S_0|X_0 = i)\]
Using first-step analysis (viz. the Markov property at time n = 1), we have
\[\varphi(i) = 0.4\varphi(i + 1) + 0.6\varphi(i - 1), i = 1, 2, 3, 4, 5, 6, 7\]
\[\varphi(0) = 0\]
\[\varphi(8) = 1\]
q <- 0.6
p <- 0.4
m <- 8
qp = q/p
for (s in 1:8) {
P = (1 - qp^s)/(1-qp^m)
print(paste0("s: " ,s," P: ", P))
#print(P)
}
## [1] "s: 1 P: 0.0203013481363997"
## [1] "s: 2 P: 0.0507533703409993"
## [1] "s: 3 P: 0.0964314036478986"
## [1] "s: 4 P: 0.164948453608248"
## [1] "s: 5 P: 0.267724028548771"
## [1] "s: 6 P: 0.421887390959556"
## [1] "s: 7 P: 0.653132434575734"
## [1] "s: 8 P: 1"
ANS: Since the prisoner bets A dollars and will lose or gain A dollars, and he bets his entire money each time until 8$. he must win each time or lose. If he wins sequence is: 1,2,4,8. He starts with 1 dollar and must win 3 bets in a row at p=0.4 p=0.4
0.4^3
## [1] 0.064
Bold strategy gives Smith a better chance to get out of jail.