from generation_manager import GenerationManager
from animal import Animal
from genes.empathetic_gene import EmpatheticGene
from genes.punisher_gene import PunisherGene
PunisherGene.type_of_punishment = "no empathy"
Animal.init_genes_class([EmpatheticGene, PunisherGene])
def action_callback(animal, animals):
""" What happen in the environnement """
assert isinstance(animal, Animal)
teammate = random.randint(0, len(animals)-1)
gain = random.uniform(-15, 5)
teammate_gain = random.uniform(-15, 5)
teammate_empathy = animals[teammate].genes["empathetic gene"].value
choice_input = {"gain":gain,
"teammate_gain":teammate_gain,
"teammate_empathy":teammate_empathy}
choice_output = animal.choose(choice_input)
if choice_output["accept_cooperation"]:
animal.reproductive_capacity += gain
animals[teammate].reproductive_capacity += teammate_gain
return True
generation_manager = GenerationManager(200)
generation_manager.action_callback = action_callback
generation_manager.run(20)
from animal import Animal
from genes.compromise_gene import CompromiseGene
Animal.init_genes_class([CompromiseGene])
def action_callback(animal, animals):
""" What happen in the environnement """
assert isinstance(animal, Animal)
teammate = random.randint(0, len(animals) - 1)
teammate_compromise = animals[teammate].genes["compromise gene"].value
choice_input = {"teammate_compromise": teammate_compromise}
choice_output = animal.choose(choice_input)
if choice_output["accept_cooperation"]:
rate = choice_output["rate"]
animal.reproductive_capacity += 2 * rate
animals[teammate].reproductive_capacity += 5 * (1 - rate)
else:
animal.reproductive_capacity += -10
animals[teammate].reproductive_capacity += -10
return True
generation_manager = GenerationManager(500)
generation_manager.action_callback = action_callback
generation_manager.run(10)
#!/bin/python """ Test how sex reproduction evolve to 50% male children and 50% female children Whatever the starting configuration, if there is no extinction, the equilibrium look like a gaussian curbe: [0, 0, 0, 0, 0, 8, 55, 148, 298, 433, 448, 338, 197, 59, 16, 0, 0, 0, 0, 0, ] """ from generation_manager import GenerationManager from animal import Animal from genes.rate_of_male_gene import RateOfMaleGene from genes.sd_gene import SDGene from genes.anti_sd_gene import Anti_SDGene Animal.init_genes_class([RateOfMaleGene]) #, SDGene, Anti_SDGene]) generation_manager = GenerationManager(2000) generation_manager.run()
PunisherGene.type_of_punishment = "no empathy"
Animal.init_genes_class([EmpatheticGene, PunisherGene])
def action_callback(animal, animals):
""" What happen in the environnement """
assert isinstance(animal, Animal)
teammate = random.randint(0, len(animals) - 1)
gain = random.uniform(-15, 5)
teammate_gain = random.uniform(-15, 5)
teammate_empathy = animals[teammate].genes["empathetic gene"].value
choice_input = {
"gain": gain,
"teammate_gain": teammate_gain,
"teammate_empathy": teammate_empathy
}
choice_output = animal.choose(choice_input)
if choice_output["accept"]:
animal.reproductive_capacity += gain
animals[teammate].reproductive_capacity += teammate_gain
return True
generation_manager = GenerationManager(200)
generation_manager.action_callback = action_callback
generation_manager.run(20)
from generation_manager import GenerationManager
from animal import Animal
from genes.compromise_gene import CompromiseGene
Animal.init_genes_class([CompromiseGene])
def action_callback(animal, animals):
""" What happen in the environnement """
assert isinstance(animal, Animal)
teammate = random.randint(0, len(animals)-1)
teammate_compromise = animals[teammate].genes["compromise gene"].value
choice_input = {"teammate_compromise":teammate_compromise}
choice_output = animal.choose(choice_input)
if choice_output["accept_cooperation"]:
rate = choice_output["rate"]
animal.reproductive_capacity += 2*rate
animals[teammate].reproductive_capacity += 5*(1-rate)
else:
animal.reproductive_capacity += -10
animals[teammate].reproductive_capacity += -10
return True
generation_manager = GenerationManager(500)
generation_manager.action_callback = action_callback
generation_manager.run(10)