248 lines
10 KiB
Python
248 lines
10 KiB
Python
from board import Board
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from player import Player
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from bot import Bot
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from restore_bot import RestoreBot
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from cup import Cup
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import numpy as np
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import sys
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import time
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class Game:
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def __init__(self, config = None):
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self.config = config
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self.board = Board.initial_state
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self.p1 = None
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self.p2 = None
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self.cup = Cup()
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def set_up_bots(self):
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self.p1 = Bot(1, config = self.config)
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self.p2 = Bot(1, config = self.config)
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def roll(self):
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return self.cup.roll()
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def roll_and_find_best_for_bot(self):
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roll = self.roll()
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move_and_val = self.p1.make_move(self.board, self.p1.get_sym(), roll)
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self.board = move_and_val[0]
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return move_and_val
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def next_round(self):
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roll = self.roll()
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#print(roll)
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self.board = Board.flip(self.p2.make_move(Board.flip(self.board), self.p2.get_sym(), roll)[0])
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return self.board
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def board_state(self):
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return self.board
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def play_against_player(self):
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self.board = Board.initial_state
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coin_flip = random.random()
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if coin_flip > 0.5:
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user_color = input("Pick a number, 1 (white) or -1 (black)")
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if int(user_color) == 1:
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p1 = Player(1)
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p2 = Bot(-1)
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else:
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p1 = Bot(1)
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p2 = Player(-1)
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else:
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p1 = Bot(1)
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p2 = Player(-1)
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# Since we have to make sure that the Bot always plays as if it's white, we have to flip
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# the board when it's not actually.
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if p1.__name__ == "Bot" and p1.get_sym() == 1:
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while Board.outcome(self.board) == None:
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roll = self.roll()
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self.board = p1.make_move(self.board, p1.get_sym(), roll)
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roll = self.roll()
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self.board = p2.make_move(self.board, p2.get_sym(), roll)
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if p1.__name__ == "Bot" and p1.get_sym() == -1:
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while Board.outcome(self.board) == None:
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roll = self.roll()
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self.board = Board.flip(p1.make_move(Board.flip(self.board), p1.get_sym(), roll))
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roll = self.roll()
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self.board = p2.make_move(self.board, p2.get_sym(), roll)
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if p2.__name__ == "Bot" and p1.get_sym() == -1:
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while Board.outcome(self.board) == None:
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roll = self.roll()
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self.board = p1.make_move(self.board, p1.get_sym(), roll)
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roll = self.roll()
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self.board = Board.flip(p2.make_move(Board.flip(self.board), p2.get_sym(), roll))
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print(Board.outcome(self.board))
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def train_model(self, episodes=1000, save_step_size = 100, trained_eps = 0):
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start_time = time.time()
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def print_time_estimate(eps_completed):
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cur_time = time.time()
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time_diff = cur_time - start_time
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eps_per_sec = eps_completed / time_diff
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secs_per_ep = time_diff / eps_completed
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eps_remaining = (episodes - eps_completed)
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sys.stderr.write("[TRAIN] Averaging {per_sec} episodes per second\n".format(per_sec = round(eps_per_sec, 2)))
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sys.stderr.write("[TRAIN] {eps_remaining} episodes remaining; approx. {time_remaining} seconds remaining\n".format(eps_remaining = eps_remaining, time_remaining = int(eps_remaining * secs_per_ep)))
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sys.stderr.write("[TRAIN] Training {} episodes and save_step_size {}\n".format(episodes, save_step_size))
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outcomes = []
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for episode in range(1, episodes + 1):
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sys.stderr.write("[TRAIN] Episode {}".format(episode + trained_eps))
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self.board = Board.initial_state
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prev_board, prev_board_value = self.roll_and_find_best_for_bot()
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# find the best move here, make this move, then change turn as the
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# first thing inside of the while loop and then call
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# roll_and_find_best_for_bot to get V_t+1
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while Board.outcome(self.board) is None:
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self.next_round()
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cur_board, cur_board_value = self.roll_and_find_best_for_bot()
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self.p1.get_network().train(prev_board, cur_board_value)
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prev_board = cur_board
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# print("-"*30)
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# print(Board.pretty(self.board))
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# print("/"*30)
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sys.stderr.write("\t outcome {}".format(Board.outcome(self.board)[1]))
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outcomes.append(Board.outcome(self.board)[1])
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final_score = np.array([ Board.outcome(self.board)[1] ]).reshape((1, 1))
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self.p1.get_network().train(prev_board, final_score)
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sys.stderr.write("\n")
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if episode % min(save_step_size, episodes) == 0:
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sys.stderr.write("[TRAIN] Saving model...\n")
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self.p1.get_network().save_model(episode+trained_eps)
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sys.stderr.write("[TRAIN] Loading model for training opponent...\n")
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self.p2.restore_model()
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if episode % 50 == 0:
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print_time_estimate(episode)
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sys.stderr.write("[TRAIN] Saving model for final episode...\n")
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self.p1.get_network().save_model(episode+trained_eps)
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self.p2.restore_model()
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return outcomes
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def next_round_test(self):
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print(self.board)
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print()
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self.next_round()
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print("--------------------------------")
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print(self.board)
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print("--------------------------------")
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def eval(self, trained_eps = 0):
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def do_eval(method, episodes = 1000, trained_eps = 0):
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start_time = time.time()
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def print_time_estimate(eps_completed):
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cur_time = time.time()
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time_diff = cur_time - start_time
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eps_per_sec = eps_completed / time_diff
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secs_per_ep = time_diff / eps_completed
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eps_remaining = (episodes - eps_completed)
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sys.stderr.write("[EVAL ] Averaging {per_sec} episodes per second\n".format(per_sec = round(eps_per_sec, 2)))
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sys.stderr.write("[EVAL ] {eps_remaining} episodes remaining; approx. {time_remaining} seconds remaining\n".format(eps_remaining = eps_remaining, time_remaining = int(eps_remaining * secs_per_ep)))
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sys.stderr.write("[EVAL ] Evaluating {eps} episode(s) with method '{method}'\n".format(eps=episodes, method=method))
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if method == 'random':
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outcomes = []
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for i in range(1, episodes + 1):
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sys.stderr.write("[EVAL ] Episode {}".format(i))
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self.board = Board.initial_state
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while Board.outcome(self.board) is None:
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roll = self.roll()
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self.board = (self.p1.make_move(self.board, self.p1.get_sym(), roll))[0]
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roll = self.roll()
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self.board = Board.flip(self.p2.make_random_move(Board.flip(self.board), self.p2.get_sym(), roll))
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sys.stderr.write("\t outcome {}".format(Board.outcome(self.board)[1]))
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outcomes.append(Board.outcome(self.board)[1])
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sys.stderr.write("\n")
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if i % 50 == 0:
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print_time_estimate(i)
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return outcomes
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elif method == 'pubeval':
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outcomes = []
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# Add the evaluation code for pubeval, the bot has a method make_pubeval_move(board, sym, roll), which can be used to get the best move according to pubeval
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for i in range(1, episodes + 1):
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sys.stderr.write("[EVAL ] Episode {}".format(i))
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self.board = Board.initial_state
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while Board.outcome(self.board) is None:
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roll = self.roll()
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self.board = (self.p1.make_move(self.board, self.p1.get_sym(), roll))[0]
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roll = self.roll()
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self.board = Board.flip(self.p2.make_pubeval_move(self.board, self.p2.get_sym(), roll)[0][0:26])
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sys.stderr.write("\t outcome {}".format(Board.outcome(self.board)[1]))
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outcomes.append(Board.outcome(self.board)[1])
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sys.stderr.write("\n")
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if i % 10 == 0:
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print_time_estimate(i)
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return outcomes
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else:
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sys.stderr.write("[EVAL ] Evaluation method '{}' is not defined\n".format(method))
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return [0]
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return [ (method, do_eval(method,
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self.config['episode_count'],
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trained_eps = trained_eps))
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for method
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in self.config['eval_methods'] ]
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def play(self, episodes = 1000):
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outcomes = []
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for i in range(episodes):
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self.board = Board.initial_state
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while Board.outcome(self.board) is None:
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# count += 1
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# print("Turn:",count)
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roll = self.roll()
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# print("type of board: ", type(self.board))
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# print("Board:",self.board)
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# print("{} rolled: {}".format(self.p1.get_sym(), roll))
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self.board = (self.p1.make_random_move(self.board, self.p1.get_sym(), roll))
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# print(self.board)
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# print()
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# count += 1
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roll = self.roll()
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# print("{} rolled: {}".format(self.p2.get_sym(), roll))
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self.board = Board.flip(self.p2.make_random_move(Board.flip(self.board), self.p2.get_sym(), roll))
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if Board.outcome(self.board)[1] > 0:
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print_winner = "1: White, " + str(Board.outcome(self.board))
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else:
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print_winner = "-1: Black " + str(Board.outcome(self.board))
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outcomes.append(Board.outcome(self.board)[1])
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print("The winner is {}!".format(print_winner))
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print("Round:",i)
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# print("Final board:",Board.pretty(self.board))
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return outcomes
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# return count
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highest = 0
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