s444409/DSZI_Survival
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Added missing docstrings

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This commit is contained in:
Marcin Kostrzewski 2020-05-17 11:22:27 +02:00
parent df16339eef
commit 96cf823619
1 changed files with 24 additions and 4 deletions
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28
src/AI/GA.py
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@ -2,7 +2,6 @@ import random
from datetime import datetime from datetime import datetime
import numpy import numpy
import copy
from src.AI.Affinities import Affinities from src.AI.Affinities import Affinities
from src.AI.ThreadedSimulation import ThreadedSimulation from src.AI.ThreadedSimulation import ThreadedSimulation
@ -11,7 +10,7 @@ from src.entities.Player import Player
from src.game.Map import Map from src.game.Map import Map
def geneticAlgorithm(map, iter, solutions, mutationAmount=0.05, multithread=False, threadCount=4): def geneticAlgorithm(map, iter, solutions, mutationAmount=0.05, multithread=False):
""" """
This algorithm will attempt to find the best affinities for player's goal choices. This algorithm will attempt to find the best affinities for player's goal choices.
@ -19,6 +18,7 @@ def geneticAlgorithm(map, iter, solutions, mutationAmount=0.05, multithread=Fals
:param iter: Generations count :param iter: Generations count
:param solutions: Solutions per generation :param solutions: Solutions per generation
:param mutationAmount: Mutation strength :param mutationAmount: Mutation strength
:param multithread: If set to true, the algorithm will run multiple threads. Not really worth it atm.
""" """
# Based on 4 weights, that are affinities tied to the player # Based on 4 weights, that are affinities tied to the player
weightsCount = 4 weightsCount = 4
@ -122,6 +122,13 @@ def crossover(genes1, genes2):
def mutation(offspring, mutationAmount): def mutation(offspring, mutationAmount):
"""
Apply a random offset to a random gene.
:param offspring: Array of offspring
:param mutationAmount: How strong the mutation is
:return: Offspring after mutation
"""
for player in offspring: for player in offspring:
randomGeneIdx = random.randrange(0, len(player)) randomGeneIdx = random.randrange(0, len(player))
player[randomGeneIdx] = player[randomGeneIdx] + random.uniform(-1.0, 1.0) * mutationAmount player[randomGeneIdx] = player[randomGeneIdx] + random.uniform(-1.0, 1.0) * mutationAmount
@ -154,6 +161,9 @@ def pickEntity(player, map):
Select an entity to become the next goal for the player. The entity is determined by Select an entity to become the next goal for the player. The entity is determined by
player's affinities and the distances between the player and entities. player's affinities and the distances between the player and entities.
Entity selection is based based on the formula:
typeWeight / (distance / walkingAffinity) * affectedStat * fixed multiplier
:param player: Player object :param player: Player object
:param map: Map object :param map: Map object
:type map: Map :type map: Map
@ -165,8 +175,8 @@ def pickEntity(player, map):
walkingAffinity = player.affinities.walking walkingAffinity = player.affinities.walking
weights = player.affinities.getWeigths() weights = player.affinities.getWeigths()
# Determine the weight of all entities based on the formula:
# typeWeight * (walkingAffinity / distance to entity) / affectedStat # Determine the weight of all entities
foodsWeights = [] foodsWeights = []
hunger = player.statistics.hunger hunger = player.statistics.hunger
for food in foods: for food in foods:
@ -213,6 +223,16 @@ def pickEntity(player, map):
def writeResults(iter, bestFit, bestMember): def writeResults(iter, bestFit, bestMember):
"""
Logs the results of the iteration to files.
The function will create two files - one that is human-readable,
and the other as Raw data used for plotting and analysis.
The output file is fixed to src/AI/resultsExplorer/.
:param iter: Current iteration index
:param bestFit: Best fitness in this generation
:param bestMember: Array of affinities of the best member in the generation
"""
if iter == 0: if iter == 0:
# Initialize human-readable log file # Initialize human-readable log file
with open("src/AI/resultsExplorer/results.txt", "w+") as f: with open("src/AI/resultsExplorer/results.txt", "w+") as f: