为什么我的代码总是用一两个字母而不是三个字母组成一个字符串？

Question

我正在学习如何使用遗传算法。我发现这个（相对地，清楚地）简单的练习让我了解了如何做的基础知识（https://blog.sicara.com/getting-started-genetic-algorithms-python-tutorial-81ffa1dd72f9）。

练习的目标是破解函数中给出的“密码”。然后它会做它的整个算法。首先，它使一组随机字符串成为“密码”的长度。

def generateOrganism(length):
  possible_chars = 'abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ1234567890'
  i = 0 
  result = ""
  while i < length:
    i += 1
    character = random.choice(possible_chars)
    result += character
  return result


def generatePopulation(sizePopulation, password):
  population = []
  print('Starting Algorithm')
  i = 0
  while i < sizePopulation:
    population.append(generateOrganism(len(password)))
    i += 1
  return population

然后检查每个单词的适应度（由单词与密码的接近程度决定），如下所示：

def fitness (password, test_word):

    if (len(test_word) != len(password)):
        print("taille incompatible")
        return
    else:
        score = 0
        i = 0
        while (i < len(password)):
            if (password[i] == test_word[i]):
                score+=1
            i+=1
        return score * 100 / len(password)

这就是所谓的 computePerfPopulation 函数，它制作一个单词及其适应度的字典。

def computePerfPopulation(population, password):
  populationPerf = {}
  for individual in population:
    populationPerf[individual] = fitness(password, individual)
    if fitness(password, individual) == 100:
      print("EUREKA, WE HAVE CRACKED THE PASSWORD. IT'S '", individual, "'")
      return 'Done'
  print(populationPerf)
  return sorted(populationPerf.items(), key = operator.itemgetter(1), reverse = True)

然后将该字典传递给 selectFromPopulation 函数，该函数选择最适合的词和一些随机词用于“繁殖”。

def selectFromPopulation(populationSorted, best_sample, lucky_few):
  nextGen = []
  for i in range(best_sample):
    nextGen.append(populationSorted[i][0])
  for i in range(lucky_few):
    nextGen.append(random.choice(populationSorted)[0])
  random.shuffle(nextGen)
  return nextGen

然后用下面的函数来孕育单词。 这就是问题所在。

def createChildren(breeders, num_of_children):
  nextPopulation = []
  for i in range(0, len(breeders) // 2):
    for j in range(0, num_of_children):
      nextPopulation.append(createChild(breeders[i], breeders[len(breeders) -1 -i]))
  print(nextPopulation)
  print(len(nextPopulation))
  return nextPopulation



def createChild(individual1, individual2):
  child = ""
  for i in range(len(individual1)):
    if (int(100) * random.random()) < 50:
      child += individual1[i]

    else:
      print(i)
      print(individual2)
      child += individual2[i]
  return child

然后一些随机词可能会被下面的函数变异，但这并不完全重要。然后整个事情循环，直到收到密码

def mutatePopulation(population, chance_mutate): # population is a list

  for i in range(len(population)):
    if int(random.random() * 100) < chance_mutate:
      population[i] = mutateWord(population[i])
  return population


def mutateWord(word):
  possible_chars = 'abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ1234567890'

  index_mods = int(random.random() * len(word))
  if index_mods == 0:
    word = random.choice(possible_chars) + word[1:]
    print(word)

  else:
    word = random.choice(possible_chars) + word[index_mods+1:]

  return word

有时整个项目会按预期运行，并且会找到“密码”。但偶尔会出现以下错误：

Traceback (most recent call last):
  File "main.py", line 146 in <module>
    project(100, 'lol' 10, 10, 5, 5)
  File "main.py", line 137 in projcet
    remakePopulation = createChildren(newBreeders, num_of_child)
  File "main.py", line 33 in createChildren
    nextPopulation.append(createChild(breeders[i], breeders[len(breeders) - 1 - 1]))
  File "main.py", line 49, in createChild
    child += individual2[i]
IndexError: string index out of range

当我调查这个问题时，我开始打印由 createChildren 函数生成的列表，（我将在下面给出整个项目代码）并注意到偶尔（在第二个循环或以上循环中，从不在第一个）一些单词会是一两个字符。我怀疑这是因为，当我再次循环它时，我将新的人口插入到 computePerfPopulation函数和新的人口与原来的人口不一样，扔掉索引？ （我希望这是有道理的）

我不知道是什么导致了问题，如果有人能告诉我发生了什么，我将不胜感激。 （我知道这很啰嗦，但请多多包涵）另外，如果您有任何关于使这段代码更好的建议，并且如果您能给我一个遗传算法实现的好资源，我将非常感激。

（如果您将所有这些代码放在此处并运行它，经过几次尝试它应该会向您显示错误等） 这是完整的项目代码：

import random
import operator


def mutatePopulation(population, chance_mutate): # population is a list

  for i in range(len(population)):
    if int(random.random() * 100) < chance_mutate:
      population[i] = mutateWord(population[i])
  return population


def mutateWord(word):
  possible_chars = 'abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ1234567890'

  index_mods = int(random.random() * len(word))
  if index_mods == 0:
    word = random.choice(possible_chars) + word[1:]
    print(word)

  else:
    word = random.choice(possible_chars) + word[index_mods+1:]

  return word




def createChildren(breeders, num_of_children):
  nextPopulation = []
  for i in range(0, len(breeders) // 2):
    for j in range(0, num_of_children):
      nextPopulation.append(createChild(breeders[i], breeders[len(breeders) -1 -i]))
  print(nextPopulation)
  print(len(nextPopulation))
  return nextPopulation



def createChild(individual1, individual2):
  child = ""
  for i in range(len(individual1)):
    if (int(100) * random.random()) < 50:
      child += individual1[i]

    else:
      print(i)
      print(individual2)
      child += individual2[i]
  return child




def selectFromPopulation(populationSorted, best_sample, lucky_few):
  nextGen = []
  for i in range(best_sample):
    nextGen.append(populationSorted[i][0])
  for i in range(lucky_few):
    nextGen.append(random.choice(populationSorted)[0])
  random.shuffle(nextGen)
  return nextGen



def computePerfPopulation(population, password):
  populationPerf = {}
  for individual in population:
    populationPerf[individual] = fitness(password, individual)
    if fitness(password, individual) == 100:
      print("EUREKA, WE HAVE CRACKED THE PASSWORD. IT'S '", individual, "'")
      return 'Done'
  print(populationPerf)
  return sorted(populationPerf.items(), key = operator.itemgetter(1), reverse = True)



def generateOrganism(length):
  possible_chars = 'abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ1234567890'
  i = 0 
  result = ""
  while i < length:
    i += 1
    character = random.choice(possible_chars)
    result += character
  return result


def generatePopulation(sizePopulation, password):
  population = []
  print('Starting Algorithm')
  i = 0
  while i < sizePopulation:
    population.append(generateOrganism(len(password)))
    i += 1
  return population



def fitness(password, test_word): # fitness function of the algorithm

  if len(test_word) != len(password):
    badFit = 0.0
    return badFit

  else:
    score = 0
    i = 0
    while i < len(password):
      if password[i] == test_word[i]:
        score += 1

      i += 1
  if test_word == password:
    print("SUCCESS")

  fit = (score * 100) / len(password)

  return fit



def project(population_size, password, best_sample, lucky_few, num_of_child, chance_of_mutation):
  password = str(password)
  population = generatePopulation(population_size, password)
  populationSorted = computePerfPopulation(population, password)
  #print(computePerfPopulation(population, password))
  breeders = selectFromPopulation(populationSorted, best_sample, lucky_few)
  nextPopulation = createChildren(breeders, num_of_child)
  nextGeneration = mutatePopulation(nextPopulation, chance_of_mutation)
  while True:
    i = 1
    newPopulationSorted = computePerfPopulation(nextGeneration, password)
    if newPopulationSorted == 'Done':
      break
    newBreeders = selectFromPopulation(newPopulationSorted, best_sample, lucky_few)
    remakePopulation = createChildren(newBreeders, num_of_child)
    nextGeneration = mutatePopulation(remakePopulation, chance_of_mutation)
    print(nextGeneration)
    print(len(nextGeneration))
    input('Press enter to continue')
    i += 1

Answer 1

在部分

def mutateWord(word):
    possible_chars = 'abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ1234567890'

可能是单个文本而不是数组？

喜欢：

def mutateWord(word):
    possible_chars = [a,b,c,d,e,f,g,h,i,j,k,l,m,n,o,p,q,r,s,t,u,v,w,x,y,z,A,B,C,D,E,F,G,H,I,J,K,L,M,N,O,P,Q,R,S,T,U,V,W,X,Y,Z,1,2,3,4,5,6,7,8,9,0]

这是一个镜头！