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| import tqdm | |
| from classes.game_model import tic_tac_toe_model | |
| from classes.Qlearningagent import QlearningAgent | |
| class environment(): | |
| def __init__(self, tic_tac_toe: tic_tac_toe_model, q_agent: QlearningAgent, train: bool, show_stats: bool): | |
| self.board = tic_tac_toe | |
| self.q_agent = q_agent | |
| self.train = train | |
| self.show_stats = show_stats | |
| def play_one_game(self, piece): | |
| game_over = False | |
| win_piece = 0 | |
| self.board.reset_matrix() | |
| if piece == 1: | |
| piece_enemy = 2 | |
| states_x = [] | |
| rewards_x = [] | |
| while not game_over: | |
| w = self.board.check_win() | |
| if w != 4: | |
| state = self.board.matriz.copy() | |
| reward_x = self.board.reward_piece(piece) | |
| state_x = (tuple(state.flatten()),-1,piece)# -1 for terminal state | |
| states_x.append(state_x) | |
| rewards_x.append(reward_x) | |
| win_piece = w | |
| break | |
| #x move and state/reward/move dynamic | |
| state = self.board.matriz.copy() | |
| avaible_moves = self.board.get_avaible_moves() | |
| action_x = self.q_agent.choose_move(state,avaible_moves,piece) | |
| i, j = self.board.number_ij(action_x) | |
| self.board.move(i,j,piece) | |
| reward_x = self.board.reward_piece(piece) | |
| state_x = (tuple(state.flatten()),action_x,piece) | |
| states_x.append(state_x) | |
| rewards_x.append(reward_x) | |
| w = self.board.check_win() | |
| if w != 4: | |
| state = self.board.matriz.copy() | |
| reward_x = self.board.reward_piece(piece) | |
| state_x = (tuple(state.flatten()),-1,piece)# -1 for terminal state | |
| states_x.append(state_x) | |
| rewards_x.append(reward_x) | |
| win_piece = w | |
| break | |
| self.board.get_random_move(piece_enemy) | |
| self.q_agent.update_q_value(states_x,rewards_x) | |
| return win_piece | |
| else: | |
| piece_enemy = 1 | |
| states_o = [] | |
| rewards_o = [] | |
| while not game_over: | |
| self.board.get_random_move(piece_enemy) | |
| w = self.board.check_win() | |
| if w != 4: | |
| state = self.board.matriz.copy() | |
| reward_o = self.board.reward_piece(piece) | |
| state_o = (tuple(state.flatten()),-1,piece)# -1 for terminal state | |
| states_o.append(state_o) | |
| rewards_o.append(reward_o) | |
| win_piece = w | |
| break | |
| state = self.board.matriz.copy() | |
| avaible_moves = self.board.get_avaible_moves() | |
| action_o = self.q_agent.choose_move(state,avaible_moves,piece) | |
| i, j = self.board.number_ij(action_o) | |
| self.board.move(i,j,piece) | |
| reward_o = self.board.reward_piece(piece) | |
| state_o = (tuple(state.flatten()), action_o, piece) | |
| states_o.append(state_o) | |
| rewards_o.append(reward_o) | |
| w = self.board.check_win() | |
| if w != 4: | |
| state = self.board.matriz.copy() | |
| reward_o = self.board.reward_piece(piece) | |
| state_o = (tuple(state.flatten()),-1,piece)# -1 for terminal state | |
| states_o.append(state_o) | |
| rewards_o.append(reward_o) | |
| win_piece = w | |
| break | |
| self.q_agent.update_q_value(states_o,rewards_o) | |
| return win_piece | |
| def play_ia_vs_ia(self): | |
| game_over = False | |
| self.board.reset_matrix() | |
| ia_x = 1 | |
| ia_o = 2 | |
| states_x = [] | |
| rewards_x = [] | |
| states_o = [] | |
| rewards_o = [] | |
| while not game_over: | |
| w = self.board.check_win() | |
| if w != 4: | |
| win_piece = w | |
| break | |
| state_x = self.board.matriz.copy() | |
| avaible_moves_x = self.board.get_avaible_moves() | |
| action_x = self.q_agent.choose_move(state_x,avaible_moves_x,ia_x) | |
| i, j = self.board.number_ij(action_x) | |
| self.board.move(i,j,ia_x) # x play | |
| #x state/reward | |
| reward_x = self.board.reward_piece(ia_x) | |
| state_x = (tuple(state_x.flatten()),action_x,ia_x) | |
| states_x.append(state_x) | |
| rewards_x.append(reward_x) | |
| w = self.board.check_win() | |
| if w != 4: | |
| win_piece = w | |
| break | |
| state_o = self.board.matriz.copy() | |
| avaible_moves_o = self.board.get_avaible_moves() | |
| action_o = self.q_agent.choose_move(state_o,avaible_moves_o,ia_o) | |
| i, j = self.board.number_ij(action_o) | |
| self.board.move(i,j,ia_o) # o play | |
| reward_o = self.board.reward_piece(ia_o) | |
| state_o = (tuple(state_o.flatten()),action_o,ia_o) | |
| states_o.append(state_o) | |
| rewards_o.append(reward_o) | |
| if win_piece == 1: | |
| state = self.board.matriz.copy() | |
| reward_o = self.board.reward_piece(ia_o) | |
| state_o = (tuple(state.flatten()),-1,ia_o)# -1 for terminal state | |
| states_o.append(state_o) | |
| rewards_o.append(reward_o) | |
| elif win_piece == 2: | |
| state = self.board.matriz.copy() | |
| reward_x = self.board.reward_piece(ia_x) | |
| state_x = (tuple(state.flatten()),-1,ia_x)# -1 for terminal state | |
| states_x.append(state_x) | |
| rewards_x.append(reward_x) | |
| self.q_agent.update_q_value(states_x,rewards_x) | |
| self.q_agent.update_q_value(states_o,rewards_o) | |
| return win_piece | |
| def run(self, n): | |
| wins_x = [] | |
| wins_o = [] | |
| wins_ia = [] | |
| if self.show_stats: | |
| print(f'Playing {n} games with X') | |
| for i in tqdm.tqdm(range(0,n)): | |
| wins_x.append(self.play_one_game(piece=1)) | |
| print(f'Playing {n} games with O') | |
| for i in tqdm.tqdm(range(0,n)): | |
| wins_o.append(self.play_one_game(piece=2)) | |
| print(f'Playing {n} games ia vs ia') | |
| for i in tqdm.tqdm(range(0,n)): | |
| wins_ia.append(self.play_ia_vs_ia()) | |
| else: | |
| for i in range(0,n): | |
| wins_x.append(self.play_one_game(piece=1)) | |
| for i in range(0,n): | |
| wins_o.append(self.play_one_game(piece=2)) | |
| for i in range(0,n): | |
| wins_ia.append(self.play_ia_vs_ia()) | |
| return wins_x,wins_o, wins_ia |