# creating new creatures.
# Based on the fitness you should select individuals for reproduction and create a
# new population. At the moment this is not done, and the same population with the same number
# of individuals
new_population = old_population
return new_population
plt.close('all')
fh=plt.figure()
# Create the world. Representaiton type choses the type of percept representation (there are three types to chose from);
# gridSize specifies the size of the world, repeatable parameter allows you to run the simulation in exactly same way.
w = World(worldType=worldType, gridSize=gridSize, repeatable=repeatableMode)
#Get the number of creatures in the world
numCreatures = w.maxNumCreatures()
#Get the number of creature percepts
numCreaturePercepts = w.numCreaturePercepts()
#Get the number of creature actions
numCreatureActions = w.numCreatureActions()
# Create a list of initial creatures - instantiations of the MyCreature class that you implemented
population = list()
for i in range(numCreatures):
c = MyCreature(numCreaturePercepts, numCreatureActions)
population.append(c)
print ("Avg FMC: %.2f" % averages[5])
print ("Avg F: %.2f" % averages[6])
print ("Avg R: %.2f" % averages[7])
print ("5 Random Chromosomes")
# print 5 random chromosomes from within the new_population
for i in range(5):
i = random.randint(0, len(new_population)-1)
myRoundedList = [ round(elem, 2) for elem in new_population[i].chromosome]
print(myRoundedList)
return new_population
# Create the world. Representaiton type choses the type of percept representation (there are three types to chose from);
# gridSize specifies the size of the world, repeatable parameter allows you to run the simulation in exactly same way.
w = World(representationType=perceptFormat, gridSize=gridSize, repeatable=repeatableMode)
#Get the number of creatures in the world
numCreatures = w.maxNumCreatures()
#Get the number of creature percepts
numCreaturePercepts = w.numCreaturePercepts()
#Get the number of creature actions
numCreatureActions = w.numCreatureActions()
# Create a list of initial creatures - instantiations of the MyCreature class that you implemented
population = list()
for i in range(numCreatures):
c = MyCreature(numCreaturePercepts, numCreatureActions)
population.append(c)
child = MyCreature(numCreaturePercepts, numCreatureActions,
chromosomeChild)
# Add it to the future population list
new_population.append(child)
#return the new population list
return new_population
# Pygame window sometime doesn't spawn unless Matplotlib figure is not created, so best to keep the following two
# calls here. You might also want to use matplotlib for plotting average fitness over generations.
plt.close('all')
fh = plt.figure()
# Create the world. The worldType specifies the type of world to use (there are two types to chose from);
# gridSize specifies the size of the world, repeatable parameter allows you to run the simulation in exactly same way.
w = World(worldType=worldType, gridSize=gridSize, repeatable=repeatableMode)
#Get the number of creatures in the world
numCreatures = w.maxNumCreatures()
#Get the number of creature percepts
numCreaturePercepts = w.numCreaturePercepts()
#Get the number of creature actions
numCreatureActions = w.numCreatureActions()
# Create a list of initial creatures - instantiations of the MyCreature class that you implemented
population = list()
for i in range(numCreatures):
c = MyCreature(numCreaturePercepts, numCreatureActions)
population.append(c)