def simulatedAnnealing(originalBoard, prob, iters = 1000, numMoves = 40):
# hill climbing, but picks worse move with given probability
bestScore = 0
bestPath = None
for i in xrange(iters):
board = deepcopy(originalBoard)
row, col, color = randomStart(board)
path = [(row, col)]
for x in xrange(numMoves):
random_num = random.random()
noDecreasingMove = False
if random_num < prob: # pick random move that decreases score
moves = decreasingMoves(board, row, col, color)
if len(moves) == 0:
noDecreasingMove = True
break
move = random.choice(moves)[0]
if random_num >= prob or noDecreasingMove is True: # pick best move
move, score = bestMove(board, row, col, color)
if move is None:
print 'THIS IS NOT SUPPOSED TO HAPPEN'
newRow, newCol = move
board[row][col] = board[newRow][newCol]
board[newRow][newCol] = color
path.append(move)
row = newRow
col = newCol
score = scoreBoard(board)
if score > bestScore:
bestScore = score
bestPath = path
return (bestPath, bestScore)
def simulatedAnnealing(originalBoard, prob, iters=1000, numMoves=40):
# hill climbing, but picks worse move with given probability
bestScore = 0
bestPath = None
for i in xrange(iters):
board = deepcopy(originalBoard)
row, col, color = randomStart(board)
path = [(row, col)]
for x in xrange(numMoves):
random_num = random.random()
noDecreasingMove = False
if random_num < prob: # pick random move that decreases score
moves = decreasingMoves(board, row, col, color)
if len(moves) == 0:
noDecreasingMove = True
break
move = random.choice(moves)[0]
if random_num >= prob or noDecreasingMove is True: # pick best move
move, score = bestMove(board, row, col, color)
if move is None:
print 'THIS IS NOT SUPPOSED TO HAPPEN'
newRow, newCol = move
board[row][col] = board[newRow][newCol]
board[newRow][newCol] = color
path.append(move)
row = newRow
col = newCol
score = scoreBoard(board)
if score > bestScore:
bestScore = score
bestPath = path
return (bestPath, bestScore)
def randomHillClimbing(originalBoard, numMoves = 40):
# picks random nondecreasing move at each state - less greedy
board = deepcopy(originalBoard)
row, col, color = randomStart(board)
path = [(row, col)]
for x in xrange(numMoves):
moves = nondecreasingMoves(board, row, col, color)
if len(moves) == 0: # score can only decrease - stop
break
move, score = random.choice(moves)
newRow, newCol = move
board[row][col] = board[newRow][newCol]
board[newRow][newCol] = color
path.append(move)
row = newRow
col = newCol
return path, scoreBoard(board)
def randomHillClimbing(originalBoard, numMoves=40):
# picks random nondecreasing move at each state - less greedy
board = deepcopy(originalBoard)
row, col, color = randomStart(board)
path = [(row, col)]
for x in xrange(numMoves):
moves = nondecreasingMoves(board, row, col, color)
if len(moves) == 0: # score can only decrease - stop
break
move, score = random.choice(moves)
newRow, newCol = move
board[row][col] = board[newRow][newCol]
board[newRow][newCol] = color
path.append(move)
row = newRow
col = newCol
return path, scoreBoard(board)
def steepestAscentHillClimbing(originalBoard, numMoves = 40):
# pick best nondecreasing move at each state - greedy
board = deepcopy(originalBoard)
row, col, color = randomStart(board)
path = [(row, col)]
for x in xrange(numMoves):
move, score = bestNondecreasingMove(board, row, col, color)
if move is None: # score can only decrease - stop
break
if len(path) > 1 and move == path[len(path) - 2]:
# looping -> stop
break
newRow, newCol = move
board[row][col] = board[newRow][newCol]
board[newRow][newCol] = color
path.append(move)
row = newRow
col = newCol
return path, scoreBoard(board)
def steepestAscentHillClimbing(originalBoard, numMoves=40):
# pick best nondecreasing move at each state - greedy
board = deepcopy(originalBoard)
row, col, color = randomStart(board)
path = [(row, col)]
for x in xrange(numMoves):
move, score = bestNondecreasingMove(board, row, col, color)
if move is None: # score can only decrease - stop
break
if len(path) > 1 and move == path[len(path) - 2]:
# looping -> stop
break
newRow, newCol = move
board[row][col] = board[newRow][newCol]
board[newRow][newCol] = color
path.append(move)
row = newRow
col = newCol
return path, scoreBoard(board)
