这对Monty Hall是好还是坏的“模拟"?怎么会? [英] Is this a good or bad 'simulation' for Monty Hall? How come?

问题描述

昨天，我们试图通过一个朋友向朋友解释蒙蒂霍尔问题，我们结束了用Python进行编码以证明如果您始终进行交换，您将赢2/3倍.我们想到了这个:

Through trying to explain the Monty Hall problem to a friend during class yesterday, we ended up coding it in Python to prove that if you always swap, you will win 2/3 times. We came up with this:

import random as r

#iterations = int(raw_input("How many iterations? >> "))
iterations = 100000

doors = ["goat", "goat", "car"]
wins = 0.0
losses = 0.0

for i in range(iterations):
    n = r.randrange(0,3)

    choice = doors[n]
    if n == 0:
        #print "You chose door 1."
        #print "Monty opens door 2. There is a goat behind this door."
        #print "You swapped to door 3."
        wins += 1
        #print "You won a " + doors[2] + "\n"
    elif n == 1:
        #print "You chose door 2."
        #print "Monty opens door 1. There is a goat behind this door."
        #print "You swapped to door 3."
        wins += 1
        #print "You won a " + doors[2] + "\n"
    elif n == 2:
        #print "You chose door 3."
        #print "Monty opens door 2. There is a goat behind this door."
        #print "You swapped to door 1."
        losses += 1
        #print "You won a " + doors[0] + "\n"
    else:
        print "You screwed up"

percentage = (wins/iterations) * 100
print "Wins: " + str(wins)
print "Losses: " + str(losses)
print "You won " + str(percentage) + "% of the time"

我的朋友认为这是解决问题的一种好方法(并且是一种很好的模拟方法)，但是我对此表示怀疑和担忧.它实际上足够随机吗?

My friend thought this was a good way of going about it (and is a good simulation for it), but I have my doubts and concerns. Is it actually random enough?

我遇到的问题是所有选择都是硬编码的.

The problem I have with it is that the all choices are kind of hard coded in.

对于Monty Hall问题，这是好是坏的模拟"?怎么会来?

您能提出更好的版本吗?

推荐答案

您的解决方案很好，但是如果您想对问题进行更严格的模拟(以及质量更高的Python ;-)，请尝试:

Your solution is fine, but if you want a stricter simulation of the problem as posed (and somewhat higher-quality Python;-), try:

import random

iterations = 100000

doors = ["goat"] * 2 + ["car"]
change_wins = 0
change_loses = 0

for i in xrange(iterations):
    random.shuffle(doors)
    # you pick door n:
    n = random.randrange(3)
    # monty picks door k, k!=n and doors[k]!="car"
    sequence = range(3)
    random.shuffle(sequence)
    for k in sequence:
        if k == n or doors[k] == "car":
            continue
    # now if you change, you lose iff doors[n]=="car"
    if doors[n] == "car":
        change_loses += 1
    else:
        change_wins += 1

print "Changing has %s wins and %s losses" % (change_wins, change_loses)
perc = (100.0 * change_wins) / (change_wins + change_loses)
print "IOW, by changing you win %.1f%% of the time" % perc

典型输出为:

Changing has 66721 wins and 33279 losses
IOW, by changing you win 66.7% of the time

这篇关于这对Monty Hall是好还是坏的“模拟"?怎么会?的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！