s444409/DSZI_Survival
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Add game mode for generating dt examples and delete unnecessary class

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This class was storing dt examples. Now they are generated to file and read from it to be used.
This commit is contained in:
Michał Czekański 2020-05-24 19:19:56 +02:00
parent 3f2e5550c7
commit 34eb74d980
5 changed files with 35 additions and 15 deletions
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0
data/AI_data/DecisionTreeExamples/dt_examples
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5
data/AI_data/dt_exmpls/dt_examples Normal file
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@ -0,0 +1,5 @@
WATER|ZERO_TO_QUARTER|HALF_TO_THREE_QUARTERS|ZERO_TO_QUARTER|GE_3_LT_8|LT_3|GE_3_LT_8
FOOD|ZERO_TO_QUARTER|QUARTER_TO_HALF|THREE_QUARTERS_TO_FULL|GE_15|GE_8_LT_15|GE_15
WATER|ZERO_TO_QUARTER|QUARTER_TO_HALF|QUARTER_TO_HALF|LT_3|GE_3_LT_8|GE_15
FOOD|HALF_TO_THREE_QUARTERS|ZERO_TO_QUARTER|QUARTER_TO_HALF|LT_3|LT_3|GE_8_LT_15
WATER|QUARTER_TO_HALF|THREE_QUARTERS_TO_FULL|QUARTER_TO_HALF|GE_8_LT_15|LT_3|GE_15

7
src/AI/DecisionTrees/projectSpecificClasses/Examples.py
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@ -1,7 +0,0 @@
from src.AI.DecisionTrees.projectSpecificClasses.SurvivalClassification import SurvivalClassification
from src.AI.DecisionTrees.projectSpecificClasses.SurvivalDTExample import SurvivalDTExample
from src.AI.DecisionTrees.projectSpecificClasses.PlayerStatsValue import PlayerStatsValue as Stats
from src.AI.DecisionTrees.projectSpecificClasses.DistFromObject import DistFromObject as Dist
examples = [
]

6
src/AI/GA_With_DT.py
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@ -4,7 +4,6 @@ from datetime import datetime
import numpy
import src.AI.DecisionTrees.InductiveDecisionTreeLearning as DT
import src.AI.DecisionTrees.projectSpecificClasses.Examples as Examples
from src.AI.Affinities import Affinities
from src.AI.DecisionTrees.DecisionTree import DecisionTree
from src.AI.DecisionTrees.projectSpecificClasses.SurvivalAttributesDefinitions import \
@ -14,17 +13,18 @@ from src.AI.SurvivalDT import SurvivalDT
from src.entities.Player import Player
def geneticAlgorithmWithDecisionTree(map, iter, solutions, mutationAmount=0.05):
def geneticAlgorithmWithDecisionTree(map, iter, solutions, decisionTreeExamples, mutationAmount=0.05):
"""
This is fusion of genetic algorithm and decision tree. Decision tree is giving travel goals for player.
:param decisionTreeExamples:
:param map: Map with all entities
:param iter: Generations count
:param solutions: Solutions per generation
:param mutationAmount: Mutation strength
"""
survivalDecisionTree = SurvivalDT(DT.inductiveDecisionTreeLearning(Examples.examples,
survivalDecisionTree = SurvivalDT(DT.inductiveDecisionTreeLearning(decisionTreeExamples,
AttrDefs.allAttributesDefinitions,
SurvivalClassification.FOOD,
SurvivalClassification))

30
src/game/Game.py
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@ -1,11 +1,13 @@
import json
from os import path
from pathlib import Path
import os
import pygame
from src.AI.Affinities import Affinities
from src.AI.DecisionTrees.DecisionTree import DecisionTree
from src.AI.DecisionTrees.ExamplesManager import ExamplesManager
from src.AI.DecisionTrees.projectSpecificClasses.SurvivalClassification import SurvivalClassification
from src.AI.GA import geneticAlgorithm
from src.entities.Player import Player
@ -14,7 +16,6 @@ from src.game.Map import Map
from src.game.Screen import Screen
from src.game.Timer import Timer
import src.AI.DecisionTrees.InductiveDecisionTreeLearning as DT
import src.AI.DecisionTrees.projectSpecificClasses.Examples as Examples
from src.AI.DecisionTrees.projectSpecificClasses.SurvivalAttributesDefinitions import \
SurvivalAttributesDefinitions as AttrDefs
from src.AI.SurvivalDT import SurvivalDT
@ -60,6 +61,7 @@ class Game:
exit(1)
elif argv[1] == "test":
self.testRun(filesPath)
# Decision tree
elif argv[1] == "dt":
if len(argv) >= 3:
if argv[2] == "-p":
@ -68,6 +70,7 @@ class Game:
else:
print("Running Decision Tree.")
self.dtRun(filesPath)
# Genetic algorithm
elif argv[1] == "ga" and len(argv) >= 3:
if len(argv) >= 4 and argv[3] == "-t":
print("Running Genetic Algorithm in multithreaded mode, iter = ", argv[2])
@ -75,10 +78,17 @@ class Game:
else:
print("Running Genetic Algorithm in singlethreaded mode, iter = ", argv[2])
self.gaRun(filesPath, int(argv[2]))
# Genetic algorithm with decision tree
elif argv[1] == "ga_dt" and len(argv) >= 3:
print("Running Genetic Algorithm with Decision Tree, iter = ", argv[2])
self.gaDTRun(filesPath, int(argv[2]))
# Generating examples for decision tree
elif argv[1] == "g_e_dt":
print("Running in mode generating examples for decision tree.")
examplesFilePath = str(filesPath) + os.sep + "data" + os.sep + "AI_data" + os.sep + "dt_exmpls" + os.sep + "dt_examples"
dtExampleManager = ExamplesManager(examplesFilePath)
dtExampleManager.generateExamples()
# Invalid game mode
else:
print("Invalid game mode. \n Possible options: test, ga")
exit(1)
@ -230,8 +240,14 @@ class Game:
print("The screen cannot be in a vertical orientation. Exiting...")
exit(1)
# Read examples to decision tree learning
examplesFilePath = str(
filesPath) + os.sep + "data" + os.sep + "AI_data" + os.sep + "dt_exmpls" + os.sep + "dt_examples"
examplesManager = ExamplesManager(examplesFilePath)
examples = examplesManager.readExamples()
# Create decision tree
survivalDecisionTree = SurvivalDT(DT.inductiveDecisionTreeLearning(Examples.examples,
survivalDecisionTree = SurvivalDT(DT.inductiveDecisionTreeLearning(examples,
AttrDefs.allAttributesDefinitions,
SurvivalClassification.FOOD,
SurvivalClassification))
@ -327,6 +343,12 @@ class Game:
# Run GA:
self.pgTimer.tick()
geneticAlgorithmWithDecisionTree(self.map, iter, 10, 0.1)
examplesFilePath = str(
filesPath) + os.sep + "data" + os.sep + "AI_data" + os.sep + "dt_exmpls" + os.sep + "dt_examples"
dtExamplesManager = ExamplesManager(examplesFilePath)
dtExamples = dtExamplesManager.readExamples()
geneticAlgorithmWithDecisionTree(self.map, iter, 10, dtExamples, 0.1)
print("Time elapsed: ", self.pgTimer.tick() // 1000)