AIME 1993 · 第 11 题
AIME 1993 — Problem 11
题目详情
Problem
Alfred and Bonnie play a game in which they take turns tossing a fair coin. The winner of a game is the first person to obtain a head. Alfred and Bonnie play this game several times with the stipulation that the loser of a game goes first in the next game. Suppose that Alfred goes first in the first game, and that the probability that he wins the sixth game is , where and are relatively prime positive integers. What are the last three digits of ?
解析
Solution
The probability that the th flip in each game occurs and is a head is . The first person wins if the coin lands heads on an odd numbered flip. So, the probability of the first person winning the game is , and the probability of the second person winning is .
Let be the probability that Alfred wins the th game, and let be the probability that Bonnie wins the th game.
If Alfred wins the th game, then the probability that Alfred wins the th game is . If Bonnie wins the th game, then the probability that Alfred wins the th game is .
Thus, .
Similarly, .
Since Alfred goes first in the st game, .
Using these recursive equations:
Since , .
Simpler Solution 1
Same as solution 1 except that . So you don't need that extra calculation for .
Solution 2 (Kind of Bashy but very nice)
In order to begin this problem, we need to calculate the probability that Alfred will win on the first round.
Because he goes first, Alfred has a chance of winning (getting heads) on his first flip.
Then, Bonnie, who goes second, has a , chance of winning on her first coin toss.
Therefore Alfred’s chance of winning on his second flip is
From this, we can see that Alfred’s (who goes first) chance of winning the first round is:
Bonnie’s (who goes second) chance of winning the first round is then .
This means that the person who goes first has a chance of winning the round, while the person who goes second has a chance of winning.
Now, through casework, we can calculate Alfred’s chance of winning the second round.
Case 1: Alfred wins twice; (Bonnie goes first this round) .
Case 2: Alfred loses the first round, but wins the second; .
Adding up the cases, we get .
Alfred, therefore, has a of winnning the second round, and Bonnie has a chance of winning this round.
From here, it is not difficult to see that the probabilities alternate in a pattern.
Make the probability that Alfred wins a round.
The chances of Alfred and Bonnie, respectively, winning the first round are and , which can be written as
The second round’s for chances are and , which can also be written as
From this, we can conclude that for the th even round, the probability that Alfred () wins can be calculated through the equation .
Solving the equation for , we get .
.
So our answer is .
Solution 3
Rather than categorizing games as wins or losses, we can categorize them as starters (S), where Alfred starts, and non-starters (NS), where Bonnie starts. Game 1 is a starter, and since Alfred must win Game 6, Game 7 is a non-starter.
As shown in Solution 1, if a player starts a certain game, the probability that they will not start the next game (i.e. win the current game) is , and the probability that they will start the next game (i.e. lose the current game) is . Similarly, if a player does not start a certain game, and . We conclude that the probability of switching from S to NS or vice versa is always , and the probability of staying the same is always .
Listing out all the games from Game 1 to Game 7, we get: S, ?, ?, ?, ?, ?, NS. Between the 7 games, there are 6 opportunities to either switch or stay the same. We need to eventually switch from S to NS, so there must be an odd number of switches. Furthermore, this number is less than 6, so it must be 1, 3, or 5.
1 switch: There are ways to place the switch, so .
3 switches: There are ways to place the switches, so .
5 switches: There are ways to place the switch, so .
Add up all these probabilities to get . , so the answer is .
Solution 4 (Probability States)
In states problems like this, it is always good to find a relation between the first game and relate it to all other games.
To do such a thing, we first develop a Markov Chain, shown below.
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Now, say is the probability Alfred wins and is the probability Bonnie wins, given that they each go first. Then, one can notice that will win either immediately with a chance of , or will lose his turn with a chance . But then, one can find a bijection that the new case is just the probability Bonnie wins, given that she goes first. However, we want Alfred to win, so the requested probability is
Similarly for ,
We can solve for any one of or , as they both will retain the same probability due to the fact they both start, and we can clearly see that solving for ;
Substituting the expression for :
in which , or , or . Thus, the probability that Alfred wins the first game given he goes first is .
Now, let be the probability that on the th game, Alfred wins. One can notice that if Alfred starts, that implies he lost the last game, and thus has a chance of winning. However, one can also notice that if Alfred goes second, then he has a chance of winning. Thus the recurrence relation
is formed.
The recurrence simplifies down to
We can bash our way to quite easily (which for the sake of spacing, I will not do). One can also calculate this explicitly, to obtain , which is in the form , and . The last three digits are .
~Pinotation