def reproduce(self, parent1: Agent, parent2: Agent) -> [Agent, Agent]:
"""
:param parent1: an Agent to generate a couple of children with another Agent
:param parent2: an Agent to generate a couple of children with another Agent
:return: a listf of 2 children (new Agents) with the new combination of the parents (Agents) genes (params)
"""
random.seed()
parent1_params = parent1.percent_first_move, \
parent1.percent_second_move, \
parent1.percent_third_move, \
parent1.percent_fourth_move \
parent2_params = parent2.percent_first_move, \
parent2.percent_second_move, \
parent2.percent_third_move, \
parent2.percent_fourth_move
index = random.randint(1, 3)
child1_params = parent1_params[:index] + parent2_params[index:]
child2_params = parent2_params[:index] + parent1_params[index:]
child1 = Agent("1", get_random_name(), 0, 0, 0, 0)
child2 = Agent("2", get_random_name(), 0, 0, 0, 0)
child1.percent_first_move, \
child1.percent_second_move, \
child1.percent_third_move, \
child1.percent_fourth_move = child1_params
child2.percent_first_move, \
child2.percent_second_move, \
child2.percent_third_move, \
child2.percent_fourth_move = child2_params
return [child1, child2]
def test_agents_play_a_game():
agent1 = Agent("1", get_random_name(), 0, 0, 0, 0)
agent2 = Agent("2", get_random_name(), 0, 0, 0, 0)
players = [agent1, agent2]
game = Connect4('cls')
game.level = 4
game.default()
game.game_mode = game.game_modes[0]
[agent1, agent2] = game.logic_play(players=players)
assert (
(agent1.record[agent1.WINS] == 1 or agent1.record[agent1.DRAWS] == 1
or agent1.record[agent1.LOSSES] == 1) and
(agent2.record[agent2.WINS] == 1 or agent2.record[agent2.DRAWS] == 1
or agent2.record[agent2.LOSSES] == 1))
def test_reproduce():
trainer = GeneticTrainer(10, 100)
parent1 = Agent("1", get_random_name(), 15, 30, 60, 90)
parent2 = Agent("2", get_random_name(), 5, 20, 50, 80)
child1, child2 = trainer.reproduce(parent1, parent2)
parent1_params, parent2_params = [15, 30, 60, 90], [5, 20, 50, 80]
child1_params = [
child1.percent_first_move, child1.percent_second_move,
child1.percent_third_move, child1.percent_fourth_move
]
child2_params = [
child2.percent_first_move,
child2.percent_second_move,
child2.percent_third_move,
child2.percent_fourth_move,
]
assert (parent1_params != child1_params
and parent2_params != child2_params)
def test_mutate():
trainer = GeneticTrainer(10, 100)
individual = Agent("1", get_random_name(), 0.14, 0.33, 0.67, 0.96)
original_params = [
individual.percent_first_move, individual.percent_second_move,
individual.percent_third_move, individual.percent_fourth_move
]
mutated = trainer.mutate(individual, 100)
mutated_params = [
mutated.percent_first_move, mutated.percent_second_move,
mutated.percent_third_move, mutated.percent_fourth_move
]
assert (original_params != mutated_params)
def generate_population(self, population_size) -> list:
"""
:param population_size: amount of individuals to be created for the new population
:return: return the randomly generated population in order to use it if required, if not, it's still kept in the
local attribute self.population
"""
for i in range(0, population_size):
random.seed()
first_percent = round(random.uniform(0, 0.25), 2)
second_percent = round(random.uniform(first_percent, 0.5), 2)
third_percent = round(random.uniform(second_percent, 0.75), 2)
fourth_percent = round(random.uniform(third_percent, 1), 2)
self.population.append(
Agent("1", get_random_name(), first_percent, second_percent,
third_percent, fourth_percent))
return self.population
def test_make_pairs():
agent1 = Agent("1", get_random_name(), 0, 0, 0, 0)
agent2 = Agent("2", get_random_name(), 0, 0, 0, 0)
agent3 = Agent("1", get_random_name(), 0, 0, 0, 0)
agent4 = Agent("2", get_random_name(), 0, 0, 0, 0)
agent5 = Agent("1", get_random_name(), 0, 0, 0, 0)
agent6 = Agent("2", get_random_name(), 0, 0, 0, 0)
agents = [agent1, agent2, agent3, agent4, agent5, agent6]
couples_in_a_row = []
for agent01, agent02 in make_pairs(agents):
couples_in_a_row.append(agent01)
couples_in_a_row.append(agent02)
assert (agents == couples_in_a_row)