def select_spouse(self, potential_spouses):
if not potential_spouses:
return None
attractions = [
self.sexual_attraction(spouse) for spouse in potential_spouses
]
return potential_spouses[utils.dist_selection(
utils.normalize_dist(attractions))]
def decide(self, state):
eps = max(
ConfigBrain.BASE_EPSILON,
1 - (self._age /
(self.learning_frequency() * ConfigBiology.MATURITY_AGE)))
brain_actions_prob = self.brain().think(state)
action_prob = utils.normalize_dist(self.fitrah() + brain_actions_prob)
decision = utils.epsilon_greedy(eps, action_prob)
return decision
def mutate_dna(dna):
memory_size = max(10, int(dna.memory_size()) + randint(-1, 1))
learning_rate = max(
np.random.normal(loc=dna.learning_rate(), scale=0.001), 1e-6)
brain_structure_param = max(
2,
dna.brain_structure_param() + randint(-1, +1))
learning_frequency = max(dna.learning_frequency() + randint(-1, 1), 1)
life_expectancy = max(0, dna.life_expectancy() + randint(-10, 10))
reward_discount = max(
0.1, min(1, np.random.normal(loc=dna.reward_discount(),
scale=0.1)))
fitrah = utils.normalize_dist(
dna.fitrah() +
np.random.normal(loc=0,
scale=ConfigBiology.EVOLUTION_MUTATION_STD,
size=dna.fitrah().size))
return DNA(memory_size, learning_rate, brain_structure_param,
learning_frequency, life_expectancy, reward_discount,
fitrah)
def race_fitrah():
return utils.normalize_dist(Human.Fitrah)
def race_fitrah():
return utils.normalize_dist(Zombie.Fitrah)
def decide(self, state):
brain_actions_prob = self._brain.think(state)
action_prob = utils.normalize_dist(
brain_actions_prob) # + self.fitrah()
decision = utils.epsilon_greedy(0, dist=action_prob)
return decision
def race_fitrah():
return utils.normalize_dist(Bacterium.Fitrah)