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ticTacToeTests.py
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# File: ticTacToeTests.py
# from chapter 18 of _Genetic Algorithms with Python_
#
# Author: Clinton Sheppard <[email protected]>
# Copyright (c) 2016 Clinton Sheppard
#
# Licensed under the Apache License, Version 2.0 (the "License").
# You may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
# implied. See the License for the specific language governing
# permissions and limitations under the License.
import datetime
import random
import unittest
from functools import partial
import genetic
def get_fitness(genes):
localCopy = genes[:]
fitness = get_fitness_for_games(localCopy)
fitness.GeneCount = len(genes)
return fitness
squareIndexes = [1, 2, 3, 4, 5, 6, 7, 8, 9]
def play1on1(xGenes, oGenes):
board = dict((i, Square(i, ContentType.Empty)) for i in range(1, 9 + 1))
empties = [v for v in board.values() if v.Content == ContentType.Empty]
roundData = [[xGenes, ContentType.Mine, genetic.CompetitionResult.Loss,
genetic.CompetitionResult.Win],
[oGenes, ContentType.Opponent, genetic.CompetitionResult.Win,
genetic.CompetitionResult.Loss]]
playerIndex = 0
while len(empties) > 0:
playerData = roundData[playerIndex]
playerIndex = 1 - playerIndex
genes, piece, lossResult, winResult = playerData
moveAndRuleIndex = get_move(genes, board, empties)
if moveAndRuleIndex is None: # could not find a move
return lossResult
index = moveAndRuleIndex[0]
board[index] = Square(index, piece)
mostRecentMoveOnly = [board[index]]
if len(RowContentFilter(piece, 3).get_matches(board, mostRecentMoveOnly)) > 0 or \
len(ColumnContentFilter(piece, 3).get_matches(board, mostRecentMoveOnly)) > 0 or \
len(DiagonalContentFilter(piece, 3).get_matches(board, mostRecentMoveOnly)) > 0:
return winResult
empties = [v for v in board.values() if v.Content == ContentType.Empty]
return genetic.CompetitionResult.Tie
def get_fitness_for_games(genes):
def getBoardString(b):
return ''.join(map(lambda i:
'.' if b[i].Content == ContentType.Empty
else 'x' if b[i].Content == ContentType.Mine
else 'o', squareIndexes))
board = dict((i, Square(i, ContentType.Empty)) for i in range(1, 9 + 1))
queue = [board]
for square in board.values():
candiateCopy = board.copy()
candiateCopy[square.Index] = Square(square.Index, ContentType.Opponent)
queue.append(candiateCopy)
winningRules = {}
wins = ties = losses = 0
while len(queue) > 0:
board = queue.pop()
boardString = getBoardString(board)
empties = [v for v in board.values() if v.Content == ContentType.Empty]
if len(empties) == 0:
ties += 1
continue
candidateIndexAndRuleIndex = get_move(genes, board, empties)
if candidateIndexAndRuleIndex is None: # could not find a move
# there are empties but didn't find a move
losses += 1
# go to next board
continue
# found at least one move
index = candidateIndexAndRuleIndex[0]
board[index] = Square(index, ContentType.Mine)
# newBoardString = getBoardString(board)
# if we now have three MINE in any ROW, COLUMN or DIAGONAL, we won
mostRecentMoveOnly = [board[index]]
if len(iHaveThreeInRow.get_matches(board, mostRecentMoveOnly)) > 0 or \
len(iHaveThreeInColumn.get_matches(board, mostRecentMoveOnly)) > 0 or \
len(iHaveThreeInDiagonal.get_matches(board, mostRecentMoveOnly)) > 0:
ruleId = candidateIndexAndRuleIndex[1]
if ruleId not in winningRules:
winningRules[ruleId] = list()
winningRules[ruleId].append(boardString)
wins += 1
# go to next board
continue
# we lose if any empties have two OPPONENT pieces in ROW, COL or DIAG
empties = [v for v in board.values() if v.Content == ContentType.Empty]
if len(opponentHasTwoInARow.get_matches(board, empties)) > 0:
losses += 1
# go to next board
continue
# queue all possible OPPONENT responses
for square in empties:
candiateCopy = board.copy()
candiateCopy[square.Index] = Square(square.Index,
ContentType.Opponent)
queue.append(candiateCopy)
return Fitness(wins, ties, losses, len(genes))
def get_move(ruleSet, board, empties, startingRuleIndex=0):
ruleSetCopy = ruleSet[:]
for ruleIndex in range(startingRuleIndex, len(ruleSetCopy)):
gene = ruleSetCopy[ruleIndex]
matches = gene.get_matches(board, empties)
if len(matches) == 0:
continue
if len(matches) == 1:
return [list(matches)[0], ruleIndex]
if len(empties) > len(matches):
empties = [e for e in empties if e.Index in matches]
return None
def display(candidate, startTime):
timeDiff = datetime.datetime.now() - startTime
localCopy = candidate.Genes[:]
for i in reversed(range(len(localCopy))):
localCopy[i] = str(localCopy[i])
print("\t{}\n{}\n{}".format(
'\n\t'.join([d for d in localCopy]),
candidate.Fitness,
timeDiff))
def mutate_add(genes, geneset):
index = random.randrange(0, len(genes) + 1) if len(genes) > 0 else 0
genes[index:index] = [random.choice(geneset)]
return True
def mutate_remove(genes):
if len(genes) < 1:
return False
del genes[random.randrange(0, len(genes))]
if len(genes) > 1 and random.randint(0, 1) == 1:
del genes[random.randrange(0, len(genes))]
return True
def mutate_replace(genes, geneset):
if len(genes) < 1:
return False
index = random.randrange(0, len(genes))
genes[index] = random.choice(geneset)
return True
def mutate_swap_adjacent(genes):
if len(genes) < 2:
return False
index = random.choice(range(len(genes) - 1))
genes[index], genes[index + 1] = genes[index + 1], genes[index]
return True
def mutate_move(genes):
if len(genes) < 3:
return False
start = random.choice(range(len(genes)))
stop = start + random.randint(1, 2)
toMove = genes[start:stop]
genes[start:stop] = []
index = random.choice(range(len(genes)))
if index >= start:
index += 1
genes[index:index] = toMove
return True
def mutate(genes, fnGetFitness, mutationOperators, mutationRoundCounts):
initialFitness = fnGetFitness(genes)
count = random.choice(mutationRoundCounts)
for i in range(1, count + 2):
copy = mutationOperators[:]
func = random.choice(copy)
while not func(genes):
copy.remove(func)
func = random.choice(copy)
if fnGetFitness(genes) > initialFitness:
mutationRoundCounts.append(i)
return
def create_geneset():
options = [[ContentType.Opponent, [0, 1, 2]],
[ContentType.Mine, [0, 1, 2]]]
geneset = [
RuleMetadata(RowContentFilter, options),
RuleMetadata(lambda expectedContent, count: TopRowFilter(), options),
RuleMetadata(lambda expectedContent, count: MiddleRowFilter(),
options),
RuleMetadata(lambda expectedContent, count: BottomRowFilter(),
options),
RuleMetadata(ColumnContentFilter, options),
RuleMetadata(lambda expectedContent, count: LeftColumnFilter(),
options),
RuleMetadata(lambda expectedContent, count: MiddleColumnFilter(),
options),
RuleMetadata(lambda expectedContent, count: RightColumnFilter(),
options),
RuleMetadata(DiagonalContentFilter, options),
RuleMetadata(lambda expectedContent, count: DiagonalLocationFilter(),
options),
RuleMetadata(lambda expectedContent, count: CornerFilter()),
RuleMetadata(lambda expectedContent, count: SideFilter()),
RuleMetadata(lambda expectedContent, count: CenterFilter()),
RuleMetadata(lambda expectedContent, count:
RowOppositeFilter(expectedContent), options,
needsSpecificContent=True),
RuleMetadata(lambda expectedContent, count: ColumnOppositeFilter(
expectedContent), options, needsSpecificContent=True),
RuleMetadata(lambda expectedContent, count: DiagonalOppositeFilter(
expectedContent), options, needsSpecificContent=True),
]
genes = list()
for gene in geneset:
genes.extend(gene.create_rules())
print("created " + str(len(genes)) + " genes")
return genes
class TicTacToeTests(unittest.TestCase):
def test_perfect_knowledge(self):
minGenes = 10
maxGenes = 20
geneset = create_geneset()
startTime = datetime.datetime.now()
def fnDisplay(candidate):
display(candidate, startTime)
def fnGetFitness(genes):
return get_fitness(genes)
mutationRoundCounts = [1]
mutationOperators = [
partial(mutate_add, geneset=geneset),
partial(mutate_replace, geneset=geneset),
mutate_remove,
mutate_swap_adjacent,
mutate_move,
]
def fnMutate(genes):
mutate(genes, fnGetFitness, mutationOperators, mutationRoundCounts)
def fnCrossover(parent, donor):
child = parent[0:int(len(parent) / 2)] + \
donor[int(len(donor) / 2):]
fnMutate(child)
return child
def fnCreate():
return random.sample(geneset, random.randrange(minGenes, maxGenes))
optimalFitness = Fitness(620, 120, 0, 11)
best = genetic.get_best(fnGetFitness, minGenes, optimalFitness, None,
fnDisplay, fnMutate, fnCreate, maxAge=500,
poolSize=20, crossover=fnCrossover)
self.assertTrue(not optimalFitness > best.Fitness)
def test_tornament(self):
minGenes = 10
maxGenes = 20
geneset = create_geneset()
startTime = datetime.datetime.now()
def fnDisplay(genes, wins, ties, losses, generation):
print("-- generation {} --".format(generation))
display(genetic.Chromosome(genes,
Fitness(wins, ties, losses, len(genes)),
None), startTime)
mutationRoundCounts = [1]
mutationOperators = [
partial(mutate_add, geneset=geneset),
partial(mutate_replace, geneset=geneset),
mutate_remove,
mutate_swap_adjacent,
mutate_move,
]
def fnMutate(genes):
mutate(genes, lambda x: 0, mutationOperators, mutationRoundCounts)
def fnCrossover(parent, donor):
child = parent[0:int(len(parent) / 2)] + \
donor[int(len(donor) / 2):]
fnMutate(child)
return child
def fnCreate():
return random.sample(geneset, random.randrange(minGenes, maxGenes))
def fnSortKey(genes, wins, ties, losses):
return -1000 * losses - ties + 1 / len(genes)
genetic.tournament(fnCreate, fnCrossover, play1on1, fnDisplay,
fnSortKey, 13)
class ContentType:
Empty = 'EMPTY'
Mine = 'MINE'
Opponent = 'OPPONENT'
class Square:
def __init__(self, index, content=ContentType.Empty):
self.Content = content
self.Index = index
self.Diagonals = []
# board layout is
# 1 2 3
# 4 5 6
# 7 8 9
self.IsCenter = False
self.IsCorner = False
self.IsSide = False
self.IsTopRow = False
self.IsMiddleRow = False
self.IsBottomRow = False
self.IsLeftColumn = False
self.IsMiddleColumn = False
self.IsRightColumn = False
self.Row = None
self.Column = None
self.DiagonalOpposite = None
self.RowOpposite = None
self.ColumnOpposite = None
if index == 1 or index == 2 or index == 3:
self.IsTopRow = True
self.Row = [1, 2, 3]
elif index == 4 or index == 5 or index == 6:
self.IsMiddleRow = True
self.Row = [4, 5, 6]
elif index == 7 or index == 8 or index == 9:
self.IsBottomRow = True
self.Row = [7, 8, 9]
if index % 3 == 1:
self.Column = [1, 4, 7]
self.IsLeftColumn = True
elif index % 3 == 2:
self.Column = [2, 5, 8]
self.IsMiddleColumn = True
elif index % 3 == 0:
self.Column = [3, 6, 9]
self.IsRightColumn = True
if index == 5:
self.IsCenter = True
else:
if index == 1 or index == 3 or index == 7 or index == 9:
self.IsCorner = True
elif index == 2 or index == 4 or index == 6 or index == 8:
self.IsSide = True
if index == 1:
self.RowOpposite = 3
self.ColumnOpposite = 7
self.DiagonalOpposite = 9
elif index == 2:
self.ColumnOpposite = 8
elif index == 3:
self.RowOpposite = 1
self.ColumnOpposite = 9
self.DiagonalOpposite = 7
elif index == 4:
self.RowOpposite = 6
elif index == 6:
self.RowOpposite = 4
elif index == 7:
self.RowOpposite = 9
self.ColumnOpposite = 1
self.DiagonalOpposite = 3
elif index == 8:
self.ColumnOpposite = 2
else: # index == 9
self.RowOpposite = 7
self.ColumnOpposite = 3
self.DiagonalOpposite = 1
if index == 1 or self.DiagonalOpposite == 1 or self.IsCenter:
self.Diagonals.append([1, 5, 9])
if index == 3 or self.DiagonalOpposite == 3 or self.IsCenter:
self.Diagonals.append([7, 5, 3])
class Rule:
def __init__(self, descriptionPrefix, expectedContent=None, count=None):
self.DescriptionPrefix = descriptionPrefix
self.ExpectedContent = expectedContent
self.Count = count
def __str__(self):
result = self.DescriptionPrefix + " "
if self.Count is not None:
result += str(self.Count) + " "
if self.ExpectedContent is not None:
result += self.ExpectedContent + " "
return result
class RuleMetadata:
def __init__(self, create, options=None, needsSpecificContent=True,
needsSpecificCount=True):
if options is None:
needsSpecificContent = False
needsSpecificCount = False
if needsSpecificCount and not needsSpecificContent:
raise ValueError('needsSpecificCount is only valid if needsSpecificContent is true')
self.create = create
self.options = options
self.needsSpecificContent = needsSpecificContent
self.needsSpecificCount = needsSpecificCount
def create_rules(self):
option = None
count = None
seen = set()
if self.needsSpecificContent:
rules = list()
for optionInfo in self.options:
option = optionInfo[0]
if self.needsSpecificCount:
optionCounts = optionInfo[1]
for count in optionCounts:
gene = self.create(option, count)
if str(gene) not in seen:
seen.add(str(gene))
rules.append(gene)
else:
gene = self.create(option, None)
if str(gene) not in seen:
seen.add(str(gene))
rules.append(gene)
return rules
else:
return [self.create(option, count)]
class ContentFilter(Rule):
def __init__(self, description, expectedContent, expectedCount,
getValueFromSquare):
super().__init__(description, expectedContent, expectedCount)
self.getValueFromSquare = getValueFromSquare
def get_matches(self, board, squares):
result = set()
for square in squares:
m = list(map(lambda i: board[i].Content,
self.getValueFromSquare(square)))
if m.count(self.ExpectedContent) == self.Count:
result.add(square.Index)
return result
class RowContentFilter(ContentFilter):
def __init__(self, expectedContent, expectedCount):
super().__init__("its ROW has", expectedContent, expectedCount,
lambda s: s.Row)
class ColumnContentFilter(ContentFilter):
def __init__(self, expectedContent, expectedCount):
super().__init__("its COLUMN has", expectedContent, expectedCount,
lambda s: s.Column)
class LocationFilter(Rule):
def __init__(self, expectedLocation, containerDescription, func):
super().__init__(
"is in " + expectedLocation + " " + containerDescription)
self.func = func
def get_matches(self, board, squares):
result = set()
for square in squares:
if self.func(square):
result.add(square.Index)
return result
class RowLocationFilter(LocationFilter):
def __init__(self, expectedLocation, func):
super().__init__(expectedLocation, "ROW", func)
class ColumnLocationFilter(LocationFilter):
def __init__(self, expectedLocation, func):
super().__init__(expectedLocation, "COLUMN", func)
class TopRowFilter(RowLocationFilter):
def __init__(self):
super().__init__("TOP", lambda square: square.IsTopRow)
class MiddleRowFilter(RowLocationFilter):
def __init__(self):
super().__init__("MIDDLE", lambda square: square.IsMiddleRow)
class BottomRowFilter(RowLocationFilter):
def __init__(self):
super().__init__("BOTTOM", lambda square: square.IsBottomRow)
class LeftColumnFilter(ColumnLocationFilter):
def __init__(self):
super().__init__("LEFT", lambda square: square.IsLeftColumn)
class MiddleColumnFilter(ColumnLocationFilter):
def __init__(self):
super().__init__("MIDDLE", lambda square: square.IsMiddleColumn)
class RightColumnFilter(ColumnLocationFilter):
def __init__(self):
super().__init__("RIGHT", lambda square: square.IsRightColumn)
class DiagonalLocationFilter(LocationFilter):
def __init__(self):
super().__init__("DIAGONAL", "",
lambda square: not (square.IsMiddleRow or
square.IsMiddleColumn) or
square.IsCenter)
class DiagonalContentFilter(Rule):
def __init__(self, expectedContent, count):
super().__init__("its DIAGONAL has", expectedContent, count)
def get_matches(self, board, squares):
result = set()
for square in squares:
for diagonal in square.Diagonals:
m = list(map(lambda i: board[i].Content, diagonal))
if m.count(self.ExpectedContent) == self.Count:
result.add(square.Index)
break
return result
class WinFilter(Rule):
def __init__(self, content):
super().__init__("WIN" if content == ContentType
.Mine else "block OPPONENT WIN")
self.rowRule = RowContentFilter(content, 2)
self.columnRule = ColumnContentFilter(content, 2)
self.diagonalRule = DiagonalContentFilter(content, 2)
def get_matches(self, board, squares):
inDiagonal = self.diagonalRule.get_matches(board, squares)
if len(inDiagonal) > 0:
return inDiagonal
inRow = self.rowRule.get_matches(board, squares)
if len(inRow) > 0:
return inRow
inColumn = self.columnRule.get_matches(board, squares)
return inColumn
class DiagonalOppositeFilter(Rule):
def __init__(self, expectedContent):
super().__init__("DIAGONAL-OPPOSITE is", expectedContent)
def get_matches(self, board, squares):
result = set()
for square in squares:
if square.DiagonalOpposite is None:
continue
if board[square.DiagonalOpposite].Content == self.ExpectedContent:
result.add(square.Index)
return result
class RowOppositeFilter(Rule):
def __init__(self, expectedContent):
super().__init__("ROW-OPPOSITE is", expectedContent)
def get_matches(self, board, squares):
result = set()
for square in squares:
if square.RowOpposite is None:
continue
if board[square.RowOpposite].Content == self.ExpectedContent:
result.add(square.Index)
return result
class ColumnOppositeFilter(Rule):
def __init__(self, expectedContent):
super().__init__("COLUMN-OPPOSITE is", expectedContent)
def get_matches(self, board, squares):
result = set()
for square in squares:
if square.ColumnOpposite is None:
continue
if board[square.ColumnOpposite].Content == self.ExpectedContent:
result.add(square.Index)
return result
class CenterFilter(Rule):
def __init__(self):
super().__init__("is in CENTER")
@staticmethod
def get_matches(board, squares):
result = set()
for square in squares:
if square.IsCenter:
result.add(square.Index)
return result
class CornerFilter(Rule):
def __init__(self):
super().__init__("is a CORNER")
@staticmethod
def get_matches(board, squares):
result = set()
for square in squares:
if square.IsCorner:
result.add(square.Index)
return result
class SideFilter(Rule):
def __init__(self):
super().__init__("is SIDE")
@staticmethod
def get_matches(board, squares):
result = set()
for square in squares:
if square.IsSide:
result.add(square.Index)
return result
iHaveThreeInRow = RowContentFilter(ContentType.Mine, 3)
iHaveThreeInColumn = ColumnContentFilter(ContentType.Mine, 3)
iHaveThreeInDiagonal = DiagonalContentFilter(ContentType.Mine, 3)
opponentHasTwoInARow = WinFilter(ContentType.Opponent)
class Fitness:
def __init__(self, wins, ties, losses, geneCount):
self.Wins = wins
self.Ties = ties
self.Losses = losses
totalGames = wins + ties + losses
percentWins = 100 * round(wins / totalGames, 3)
percentLosses = 100 * round(losses / totalGames, 3)
percentTies = 100 * round(ties / totalGames, 3)
self.PercentTies = percentTies
self.PercentWins = percentWins
self.PercentLosses = percentLosses
self.GeneCount = geneCount
def __gt__(self, other):
if self.PercentLosses != other.PercentLosses:
return self.PercentLosses < other.PercentLosses
if self.Losses > 0:
return False
if self.Ties != other.Ties:
return self.Ties < other.Ties
return self.GeneCount < other.GeneCount
def __str__(self):
return "{:.1f}% Losses ({}), {:.1f}% Ties ({}), {:.1f}% Wins ({}), {} rules".format(
self.PercentLosses,
self.Losses,
self.PercentTies,
self.Ties,
self.PercentWins,
self.Wins,
self.GeneCount)
if __name__ == '__main__':
unittest.main()