possible_board_states = [
game.pretend_to_move_piece(move.oldLoc, move.newLoc)
for move in possible_moves_lst
]
possible_state_vecs = [
state.get_alt_state_vec() for state in possible_board_states
]
scores = [model.predict(vec)[0, 0] for vec in possible_state_vecs]
return possible_moves_lst[max_index(scores)]
if __name__ == "__main__":
while not game.is_game_over()[0]:
if game.current_turn == 1:
best_move = get_moves_computer(thing_1)
game.move_piece(best_move.oldLoc, best_move.newLoc)
else:
if HUMAN_PLAYING:
piece, move = get_moves_human()
game.move_piece(piece, move)
else:
game.flip_board_nocopy() # flip it for use
best_move = get_moves_computer(thing_2)
print("Iteration:", super_itr)
thing1_data = []
thing2_data = []
for i in range(games_per_itr): # play multiple games
should_display_game_results = i == games_per_itr - 1
game = CheckerBoard()
game.scramble()
thing1_state_vecs = []
thing2_state_vecs = []
# by flippping the board we switch teams but actually stay on team 1 according to the game object
team_for_real = 1
moves_taken = 0
while not game.is_game_over()[0]: # play 1 game
moves = game.get_all_possible_moves()
possible_moves_lst = []
for piece, possible_piece_moves in moves.items():
for possible_piece_move in possible_piece_moves:
possible_moves_lst.append(Move(piece, possible_piece_move))
random.shuffle(possible_moves_lst)
possible_board_states = [game.pretend_to_move_piece(move.oldLoc, move.newLoc) for move in
possible_moves_lst]
possible_state_vecs = [state.get_alt_state_vec() for state in possible_board_states]