def playPyramido(human=0, iterations=1000):
movenumber = 1
position = PyramidoPosition(toArray(1))
player = 1
while possible_moves(position):
if player == human:
position = humanPickMove(position)
else:
position = computerPickMove(position, iterations)
print('Move %d: Player %d moves to\n%s'
% (movenumber, player, str(position)))
movenumber += 1
player = 3 - player
def policy(position):
moves = possible_moves(position)
if not moves:
return {}, leaf_node_value(position)
moves_nn_format = [m.nn_format() for m in moves]
scores = y.eval(feed_dict={
x: moves_nn_format,
keep_prob: 1.0
}).flatten()
probability = {}
for i, m in enumerate(moves):
probability[m] = scores[i]
return probability, max(probability.values())
def generate_one_game(policy, num_iterations=100):
x = []
y_ = []
position = PyramidoPosition(toArray(1))
movenumber = 1
player = 1
while possible_moves(position):
dist, _ = MCTS(policy, position, num_iterations)
max_probability = max(dist.values())
for move, probability in dist.items():
x.append(move)
y_.append(probability)
if probability == max_probability:
position = move
print('Move %d: Player %d moves with value %f to\n%s' %
(movenumber, player, probability, str(position)))
movenumber, player = movenumber + 1, 3 - player
return zip(x, y_)
def pyramido_policy(position):
moves = possible_moves(position) # game must define this
bottom_row_moves = []
other_moves = []
for m in moves:
if np.logical_and.reduce(m.array()[0] == position.array()[0]):
other_moves.append(m)
else:
bottom_row_moves.append(m)
bottom_row_weight = 1.0
if not other_moves:
bottom_row_weight = 1.0
if not bottom_row_moves:
bottom_row_weight = 0.0
distribution = {}
for m in bottom_row_moves:
distribution[m] = bottom_row_weight / len(bottom_row_moves)
for m in other_moves:
distribution[m] = (1.0 - bottom_row_weight) / len(other_moves)
return distribution, val(position)
def pol(position):
distribution = {}
moves = possible_moves(position) # game must define this
for m in moves:
distribution[m] = 1.0 / len(moves)
return distribution, val(position)
def humanPickMove(position):
moves = possible_moves(position)
for i, m in enumerate(moves):
print('Option %d:\n%s\n' % (i, str(m)))
selection = int(input('Selection:\n'))
return moves[selection]