Closed Jonyian closed 1 year ago
同求,其次运行文件中的run_maacktr.py和run_mappo.py都会以下错误,可以提供一下解决方案吗?感谢
ERROR:root:Can not find checkpoint for ./results/Sep_19_12_22_29/models/
H:\Code-of-study\PaperCode\MARL_CAVs-main\MARL\single_agent\kfac.py:144: UserWarning: volatile was removed (Variable.volatile is always False)
if input[0].volatile == False and self.steps % self.Ts == 0:
H:\ProgramData\Anaconda3\envs\MARL_CAVs-main\lib\site-packages\torch\nn\modules\module.py:795: UserWarning: Using a non-full backward hook when the forward contains multiple autograd Nodes is deprecated and will be removed in future versions. This hook will be missing some grad_input. Please use register_full_backward_hook to get the documented behavior.
warnings.warn("Using a non-full backward hook when the forward contains multiple autograd Nodes "
H:\Code-of-study\PaperCode\MARL_CAVs-main\MARL\single_agent\Model_common.py:62: UserWarning: Implicit dimension choice for log_softmax has been deprecated. Change the call to include dim=X as an argument.
act = self.actor_output_act(self.actor_linear(out))
Traceback (most recent call last):
File "H:\Code-of-study\PaperCode\MARL_CAVs-main\MARL\run_maacktr.py", line 217, in
@Jonyian @BigZhaoHYZ , please find the codes at: https://drive.google.com/drive/folders/1CPOOYSQzqc0_XUr8durNWDUBv66PUHaM
@BigZhaoHYZ , please look at the solution at: https://github.com/DongChen06/MARL_CAVs/issues/4. The reason may be the mismatch of the libs.
Thank you very much for your reply. I also want to ask you a question. Is the baseline of your paper the run_ma2c.py in the folder?
You can change the settings in configs.ini. For example, you can set safety_gurantee as False. ;
There are also other settings you can play with:
; concurrent
training_strategy = concurrent
actor_hidden_size = 128
critic_hidden_size = 128
shared_network = True
action_masking = True
state_split = True
; "greedy", "regionalR", "global_R"
reward_type = regionalR
safety_guarantee = True n_step = 7
你好,运行run_ma2c.py
加上configs.ini
就是论文中的“基线+Tn”吗?感谢回复! @DongChen06
@BigZhaoHYZ Yes, you are right
Thank you very much for your reply
Could you please open source the “ours” algorithm mentioned in your paper?