def getRandomTerminalTicTacToeState():
ttt = TicTacToe(4)
while not isTicTacToeStateTerminal(ttt):
ttt.make_move(getRandomAction(ttt.get_possible_moves()))
return ttt
class TicTacToeDecisionTreeAgent:
def __init__(self):
self.__possible_actions = []
self.__tictactoe = TicTacToe(4)
self.__training_set = self.__read_tictactoe_training_set(
TICTACTOE_TRAINING_SET)
@property
def training_set(self):
return self.__training_set
def get_action_decision(self, tictactoe_state):
self.__tictactoe = tictactoe_state
self.__possible_actions = self.__tictactoe.get_possible_moves()
# TODO dont return random action, return strategic action
random_action = randint(0, (len(self.__possible_actions) - 1))
return self.__possible_actions[random_action]
def receive_reward(self, reward, action_sequence):
if reward != '' and action_sequence != []:
self.__create_tictactoe_agent_experience_file_if_not_exist()
with open(TICTACTOE_AGENT_EXPERIENCE, "a") as text_file:
white_space_buffer = 16 - len(action_sequence)
self.__write_every_element_in_list_to_open_textfile(
text_file, action_sequence)
text_file.write(
"{}\n".format((" |" * white_space_buffer) + reward))
def __create_tictactoe_agent_experience_file_if_not_exist(self):
if not os.path.isfile(TICTACTOE_AGENT_EXPERIENCE):
with open(TICTACTOE_AGENT_EXPERIENCE, "w") as text_file:
column_label = "LvL 1 |LvL 2 |LvL 3 |LvL 4 |LvL 5 |LvL 6 |LvL 7 |LvL 8 |LvL 9 |LvL 10|LvL 11|LvL 12|LvL 13|LvL 14|LvL 15|LvL 16|Target Value"
table_limits = "______|______|______|______|______|______|______|______|______|______|______|______|______|______|______|______|____________"
text_file.write("{}\n".format(column_label))
text_file.write("{}\n".format(table_limits))
def __write_every_element_in_list_to_open_textfile(self, open_textfile,
list):
for element in list:
open_textfile.write("{}|".format(str(element)))
def __read_tictactoe_training_set(self, training_set_filename):
with open(training_set_filename, "r") as text_file:
results = []
list_of_sequences = []
text_file.readline()
text_file.readline()
for line in text_file.readlines():
list_of_sequences.append(line.strip('\n').split('|'))
for sequence in list_of_sequences:
target_value = sequence.pop()
results.append((sequence, target_value))
return results
def count_target_value_appearance(self):
count_of_target_value_appearance = {"wins": 0, "loses": 0, "draws": 0}
for target_value in self.training_set:
if target_value[1] == "win":
count_of_target_value_appearance["wins"] += 1
elif target_value[1] == "lost":
count_of_target_value_appearance["loses"] += 1
elif target_value[1] == "draw":
count_of_target_value_appearance["draws"] += 1
return count_of_target_value_appearance
def count_level_appearance(self):
length_of_action_sequences = []
count_of_level_appearance = {
7: 0,
8: 0,
9: 0,
10: 0,
11: 0,
12: 0,
13: 0,
14: 0,
15: 0,
16: 0
}
for action_sequence in self.training_set:
action_sequence = [
element for element in action_sequence[0]
if element != ' '
]
length_of_action_sequences.append(len(action_sequence))
for length_index in range(7, 17):
count_of_level_appearance[
length_index] = length_of_action_sequences.count(length_index)
return count_of_level_appearance
def count_target_value_appearance_inside_levels(self):
list_of_aciton_sequence_length_and_target_value = []
target_values_in_level = {
7: {
"wins": 0,
"loses": 0,
"draws": 0
},
8: {
"wins": 0,
"loses": 0,
"draws": 0
},
9: {
"wins": 0,
"loses": 0,
"draws": 0
},
10: {
"wins": 0,
"loses": 0,
"draws": 0
},
11: {
"wins": 0,
"loses": 0,
"draws": 0
},
12: {
"wins": 0,
"loses": 0,
"draws": 0
},
13: {
"wins": 0,
"loses": 0,
"draws": 0
},
14: {
"wins": 0,
"loses": 0,
"draws": 0
},
15: {
"wins": 0,
"loses": 0,
"draws": 0
},
16: {
"wins": 0,
"loses": 0,
"draws": 0
}
}
for set in self.training_set:
list_of_aciton_sequence_length_and_target_value.append(
(len([element for element in set[0]
if element != ' ']), set[1]))
for length_index in range(7, 17):
target_values_in_level[length_index][
"wins"] = list_of_aciton_sequence_length_and_target_value.count(
(length_index, "win"))
target_values_in_level[length_index][
"loses"] = list_of_aciton_sequence_length_and_target_value.count(
(length_index, "lost"))
target_values_in_level[length_index][
"draws"] = list_of_aciton_sequence_length_and_target_value.count(
(length_index, "draw"))
return target_values_in_level