Deciding to put probability theory to good use, we encounter a slot machine with three independent wheels, each producing one of the four symbols BAR, BELL, LEMON, or CHERRY with equal probability. The slot machine has the following payout scheme for a bet of 1 coin (where "?" denotes that we don't care what comes up for that wheel):
BAR/BAR/BAR pays 20 coins BELL/BELL/BELL pays 15 coins LEMON/LEMON/LEMON pays 5 coins CHERRY/CHERRY/CHERRY pays 3 coins CHERRY/CHERRY/? pays 2 coins CHERRY/?/? pays 1 coin
a. Compute the expected "payback" percentage of the machine. In other words, for each coin played, what is the expected coin return?
b. Compute the probability that playing the slot machine once will result in a win. c. Estimate the mean and median number of plays you can expect to make until you go broke, if you start with 10 coins. You can run a simulation to estimate this, rather than
trying to compute an exact answer.
(Artificial Intelligence: A Modern Approach, 3rd Edition. Prentice Hall/CourseSmart, 12/01/2009. p. 507).