def main():
for iteration in range(ITERATION):
print("Iteration: " + str(iteration + 1))
start = time.time()
step = 0
matrix = np.zeros((4, 4), dtype=np.int)
matrix = logic.add_two(matrix)
while True:
matrix = logic.add_two(matrix)
if logic.game_state(matrix) == 'lose':
break
if logic.game_state(matrix) == 'lose':
break
matrix = montecarlo.getMove(matrix, NUM_BACKGROUND_RUNS)
step += 1
# move=montecarlo.getMove(matrix, NUM_BACKGROUND_RUNS)
# # print("got a move " + str(move))
# matrix=montecarlo.moveGrid(matrix,move)
# step+=1
print(matrix)
print("Step= " + str(step))
print("Max= " + str(2**np.max(matrix)))
print("Score= " + str(logic.getScore(matrix)))
print('Depth= ' + str(NUM_BACKGROUND_RUNS))
print('Time= ' + str(time.time() - start))
print('')
stat.append((step, 2**np.max(matrix), logic.getScore(matrix)))
def main():
for iteration in range(ITERATION):
print("Iternaton: " + str(iteration + 1))
step = 0
matrix = np.zeros((4, 4))
matrix = logic.add_two(matrix)
while True:
matrix = logic.add_two(matrix)
if logic.game_state(matrix) == 'lose':
break
while True:
move = ExpectiMax.getMove(matrix, DEPTH)
if move == "'w'":
newMatrix, _ = logic.up(matrix)
if move == "'a'":
newMatrix, _ = logic.left(matrix)
if move == "'s'":
newMatrix, _ = logic.down(matrix)
if move == "'d'":
newMatrix, _ = logic.right(matrix)
if ExpectiMax.isSame(newMatrix, matrix) == False:
matrix = newMatrix
break
step += 1
print("Step= " + str(step))
print("Max= " + str(np.max(matrix)))
print("Score= " + str(logic.getScore(matrix)))
print('')
stat.append((step, np.max(matrix), logic.getScore(matrix)))
np.savetxt("stat.txt", stat)
def expectiMax(grid, agent, depth):
score = 0
if (logic.game_state(grid) == 'lose'):
return FAIL_SCORE
if depth == 0:
return logic.getScore(grid) * getUtility(grid)
# Player's turn
if agent == 0:
for i in range(4):
newGrid = moveGrid(grid, i)
score = max(score, expectiMax(newGrid, 1, depth))
return score
# Computer's turn
elif agent == 1:
count = 0
score = 0
for i in range(4):
for j in range(4):
if grid[i][j] == 0:
grid[i][j] = 2
count += 1
score += expectiMax(grid, 0, depth - 1)
grid[i][j] = 0
if count == 0:
return FAIL_SCORE
else:
return score / count
def main():
for iteration in range(ITERATION):
print("Iteration: " + str(iteration + 1))
start = time.time()
step = 0
matrix = logic.new_game()
matrix = logic.add_two(matrix)
while True:
matrix = logic.add_two(matrix)
if logic.gameOver(matrix):
break
# print("given this board")
# logic.printBoard(matrix)
move = ExpectiMax.getMove(matrix, DEPTH)
matrix = ExpectiMax.moveGrid(matrix, move)
# print("expectimax recommends this move " + str(move))
# print("resulting in this board")
# logic.printBoard(matrix)
step += 1
print("Step= " + str(step))
print("Max= " + str(2**logic.getMax(matrix)))
print("Score= " + str(logic.getScore(matrix)))
print('Depth= ' + str(DEPTH))
print('Time= ' + str(time.time() - start))
print('')
def randomPolicyUntilGameOver(grid, numBackgroundRuns):
score = 0
for i in range(numBackgroundRuns):
curGrid = grid.copy()
while True:
curGrid = logic.add_two(curGrid)
board_list = randomMove(curGrid)
if not board_list:
break
curGrid = random.choice(board_list)
score += logic.getScore(curGrid)
return score
def iteration(iter):
start = time.time()
step = 0
matrix = np.zeros((4, 4), dtype=np.int)
matrix = logic.add_two(matrix)
while True:
matrix = logic.add_two(matrix)
if logic.game_state(matrix) == 'lose':
break
move = ExpectiMax.getMove(matrix, DEPTH)
matrix = ExpectiMax.moveGrid(matrix, move)
step += 1
print("Iteration: " + str(iter + 1))
print("Step= " + str(step))
print("Max= " + str(2**np.max(matrix)))
print("Score= " + str(logic.getScore(matrix)))
print('Depth= ' + str(DEPTH))
print('Time= ' + str(time.time() - start))
print('')
return (step, 2**np.max(matrix), logic.getScore(matrix))
def displayCorrection(questionsNode, answer):
# Check if answer is correct:
category = logic.getCategory(questionsNode)
question = logic.getQuestion(questionsNode)
if logic.checkAnswer(category, question, answer) == True:
print("Correct!")
# Makes correction if incorrect
else:
correctAnswer = logic.getCorrectAnswer(questionsNode)
reference = logic.getReference(questionsNode)
print("Incorrect (-$4). The correct answer was " + correctAnswer) # + answer from json
print("You can learn about this topic here: " + reference)
score = logic.getScore()
print("Your total sum is now $" + str(score["balance"]))
def displayResult():
#todo 3: display the final game result"
score = logic.getScore()
balance = score["balance"]
budget = str(round(score["budget"] * 100.0, 1))
bill = str(round(score["bill"] * 100.0, 1))
loans = str(round(score["loans"] * 100.0, 1))
credit = str(round(score["credit"] * 100.0,1))
invest = str(round(score["invest"] * 100.0,1))
print("Congratulations, you have completed the exam! You have $" + str(balance) + " left")
print("... you lost $" + str((100 - balance)))
# or instead say how much money you lost (or both?)?
print("Here is your breakdown percent correct by category: ")
print(" Budgeting and setting financial goals: " + budget + "%")
print(" Paying bills, taxes, and saving money: " + bill + "%")
print(" Loans................................: " + loans + "%")
print(" Credit...............................: " + credit + "%")
print(" Investing, 401(k)s, and stocks.......: " + invest + "%")
def alphaBetaPruning(grid, agent, depth, alpha, beta):
# base case
if (logic.game_state(grid) == 'lose'):
return FAIL_SCORE
if depth == 0:
return logic.getScore(grid)
# Player's turn
if agent == 0:
score = 0
for i in range(4):
newGrid = moveGrid(grid, i)
futureScore = alphaBetaPruning(newGrid, 1, depth, alpha, beta)
# new score should be in range [alpha, beta]
if futureScore > beta:
return futureScore
alpha = max(alpha, futureScore) # update alpha/lower bound
score = max(score, futureScore)
return score
# Computer's turn
elif agent == 1:
count = 0
score = float('inf')
for i in range(4):
for j in range(4):
if (grid[i][j] == 0): # for each cell with a 0
grid[i][j] = 2 # create a 2 tile
count += 1
futureScore = alphaBetaPruning(grid, 0, depth - 1,
alpha,
beta) # agent goes next
# new score should be in range [alpha, beta]
if futureScore < alpha:
return futureScore
beta = min(beta,
futureScore) # update beta/upper bound
score = min(score, futureScore)
grid[i][j] = 0 # reset the 2 tile back to 0
if count == 0: # if no cell with 0 val, fail
return FAIL_SCORE
else:
return score
def main():
f = open("expectimax2.txt", "w+")
for iteration in range(ITERATION):
print("Iteration: " + str(iteration + 1))
start = time.time()
step = 0
matrix = np.zeros((4, 4), dtype=np.int)
matrix = logic.add_two(matrix)
while True:
matrix = logic.add_two(matrix)
if logic.game_state(matrix) == 'lose':
break
move = ExpectiMax.getMove(matrix, DEPTH)
matrix = ExpectiMax.moveGrid(matrix, move)
step += 1
f.write("Step %d, max %d, Score %d, \r\n" %
(step, 2**np.max(matrix), logic.getScore(matrix)))
f.flush()
f.close()
