def conceive(self, mother: Genome, father: Genome,
prisoner_cb: Callable[[Prisoner], None]) -> None:
# Construct duplicates of the mother and father.
mother = Genome(mother.genes)
father = Genome(father.genes)
# Perform a uniform crossover.
mother.crossover(father, Genetics.__uniform_crossover)
# Mutate both sets of genes.
mother.mutate(self.__uniform_mutation)
father.mutate(self.__uniform_mutation)
# Pass the two children to the callback.
prisoner_cb(Prisoner(mother))
prisoner_cb(Prisoner(father))
class Player:
def __init__(self):
assert INPUTS != 0 and OUTPUTS != 0, "You must call the initialize method before creating players!"
self.fitness = -1
self.unadjustedFitness = -1
self.brain = Genome(INPUTS, OUTPUTS, False)
self.vision = []
self.actions = []
self.lifespan = 0
self.dead = False
self.replay = False
self.gen = 0
self.name = ""
self.speciesName = "Not yet defined"
def update(self):
# Does something that will eventually end up in death or victory
# for the organism
pass
def look(self):
# Looks at the input - This is where you should populate your vision
# array
pass
def think(self):
# Makes actions based off of input
# Fill in based off of what you want to happen
pass
def clone(self):
out = Player()
out.replay = False
out.fitness = self.fitness
out.gen = self.gen
out.brain = self.brain.clone()
return out
def cloneForReplay(self):
out = Player()
out.replay = True
out.fitness = self.fitness
out.brain = self.brain.clone()
out.speciesName = self.speciesName
def calculateFitness(self):
# To return the calculated fitness at any given point in time
pass
def getFitness(self):
if not self.replay:
return self.calculateFitness()
return self.fitness
def crossover(self, parent2):
child = Player()
child.brain = self.brain.crossover(parent2.brain)
child.brain.generateNetwork()
return child
