Op = Control()
print('\n collecting experience...')
if os.path.exists('./model/model_gpu_dqn.check'):
dqn.load()
total_step = 0
for i_episode in range(1000):
Op.getstate()
while True:
action = dqn.choose_action(Op.state)
# 执行行为
state_next, reward, terminal = Op.action(action)
if terminal:
break
dqn.store_transition(Op.state, action, reward, state_next)
if dqn.memory_counter > Memory_capacity:
dqn.learn()
print(
f'Ep:{i_episode} | Ep_r:{round(reward,3)} | total_step:{total_step}'
)
if total_step == 50000:
dqn.save()
sys.exit()
if i_episode % 50 == 0:
dqn.save()
# 总执行步数加1
total_step += 1
# 获取下一个state
Op.state = state_next
