def test_game(self, enemy="opp", verbose=False, player1_starts=True):
c4 = Game(self.height, self.width, on_move=1 if player1_starts else -1)
while c4.winner is None:
if player1_starts:
move, q_max = c4.best_next_move(self.qnet)
c4.play(move)
print_cond(c4.field,
"\nplayer 1 (qnet) played",
move,
cond=verbose)
player1_starts = True
if c4.winner is None:
if enemy == "qnet":
move, q_max = c4.best_next_move(self.qnet)
elif enemy == "opp":
move = self.ais[-1].next_move(c4)
elif enemy == "rand":
move = np.random.choice(c4.possible_moves())
elif enemy == "human":
print("Current Field state:\n", c4.field)
move = int(input("Your move: " + str(c4.possible_moves())))
print_cond("player -1", enemy, "played", move, cond=verbose)
c4.play(move)
return c4.winner
def next_move(self, c4: Game):
if c4.lastMove is not None:
vicinty = list(
set(c4.possible_moves()).intersection(
range(c4.lastMove - 1, c4.lastMove + 2)))
if len(vicinty) > 0:
return np.random.choice(vicinty)
return np.random.choice(c4.possible_moves())
def next_exploring_move(self, c4: Game, epsilon=0.2):
assert c4.on_move == self.color
explore = np.random.rand() < epsilon
if explore:
move = np.random.choice(c4.possible_moves())
else:
move = self.next_move(c4)
return move, {"explore": explore}
def next_move(self, c4: Game):
if c4.lastMove is not None and c4.lastMove in c4.possible_moves():
return c4.lastMove
else:
return np.random.choice(c4.possible_moves())
def next_move(self, c4: Game):
return np.random.choice(c4.possible_moves())