print("番号を入力してください")
print(enables)
inp = input('>>> ')
action_t = int(inp)
for i in enables:
if action_t == i:
flg = True
break
env.update(action_t, 1)
else:
print("パス")
if env.isEnd() == True: break
print("*** AIターン● ***")
env.print_screen()
enables = env.get_enables(2)
if len(enables) > 0:
qvalue, action_t = agent.select_enable_action(env.screen, enables)
print('>>> {:}'.format(action_t))
env.update(action_t, 2)
else:
print("パス")
print("*** ゲーム終了 ***")
if env.winner() == 1:
print("あなたの勝ち！ スコアは、{:}です。".format(env.get_score(1)))
else:
print("あなたの負け！ AIのスコアは、{:}です。".format(env.get_score(2)))
if win == playerID[j]:
# 勝ったら報酬1を得る
reword = 1
players[j].store_experience(
state, targets, tr, reword, state_X, target_X,
end)
players[j].experience_replay()
# 行動を選択
action = players[i].select_action(state, targets,
players[i].exploration)
# 行動を実行
env.update(action, playerID[i])
# for log
loss = players[i].current_loss
Q_max, Q_action = players[i].select_enable_action(
state, targets)
print(
"player:{:1d} | pos:{:2d} | LOSS: {:.4f} | Q_MAX: {:.4f}"
.format(playerID[i], action, loss, Q_max))
# 行動を実行した結果
terminal = env.isEnd()
w = env.winner()
print("EPOCH: {:03d}/{:03d} | WIN: player{:1d}".format(e, n_epochs, w))
# 保存は後攻のplayer2 を保存する。
players[1].save_model()
for i in range(0, 2):
state = env.screen # 현재 보드판의 상태(배열)을 가져옴
targets = env.getEnables(
playerID[i]) # 배열(플레이어가 둘 수 있는 위치를 가짐)을 가져옴
if len(targets) > 0: # 어딘가에 둘 수 있는 장소가있는 경우
# 행동을 선택
action = players[i].selectAction(state, targets,
1 / ((e / 10) + 1))
# 행동을 실행
env.doFlip([action // 8, action % 8], playerID[i])
# 종료 판정
win = env.winner() # 현재 유리한 플레이어
end = env.isEnd()
# 다음 상태
state_X = env.screen
target_X = env.getEnables(playerID[i + 1])
if len(target_X) == 0:
target_X = env.getEnables(playerID[i])
reward = 0
if end == True:
reward = 1
players[i].storeExperience(state, targets, action, reward,
state_X, target_X, end)
