class Environment(object):
def __init__(self):
self.S = TwentyFortyEight()
self.S.make_tables()
self.score = 0
self.S.new_tile()
print("New Episode")
def reset(self):
self.S.score = 0
self.S.cells = 0
self.score = 0
self.S.new_tile()
return self.S.vectorize_state()
def step(self, action):
score_prev = self.S.score1()
cells = self.S.cells
self.S.move(action + 1)
r = self.S.score1() - score_prev
self.score = self.S.score1()
if not cells == self.S.cells:
self.S.new_tile()
if not self.S.canMove():
return self.S.vectorize_state(), r, True
return self.S.vectorize_state(), r, False
def seed(self, a):
return
# print(dir)
# print("Score:"+str(x.score)+"\t Max Tile:"+str(x.maxValue()))
# x.move(dir)
# x.new_tile()
# # print("GAME ENDs")
# # print(x.maxValue())
# print("Score:"+str(x.score)+"\t Max Tile:"+str(x.maxValue()))
# # x.__str__()
# # print(x.get_available_moves())
occ = np.zeros(16)
for i in range(500):
x=TwentyFortyEight()
x.make_tables()
# x.print_tables()
# print("Generated Tables")
x.new_tile()
# avail_moves = x.get_available_moves()
while(True):
# x.__str__()
# print("-----------------------")
temp = x.vectorize_state();
tempx = np.zeros((1, 256))
for j in range(16):
tempx[0, j*16 + temp[j]] = 1
probs=y.eval(feed_dict={x1: tempx})[0]
# print(probs)
# dir = eminimax(x,2)
