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demo_A2C_PPO #354
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D:\anconda\envs\pytorch\python.exe C:\Users\user\Desktop\ElegantRL-master\examples\demo_A2C_PPO.py
env_args = {'env_name': 'CartPole-v1',
'num_envs': 1,
'max_step': 500,
'state_dim': 4,
'action_dim': 2,
'if_discrete': True}
| Arguments Remove cwd: ./CartPole-v1_DiscreteA2C_0
| Evaluator:
|
step
: Number of samples, or total training steps, or running times ofenv.step()
.|
time
: Time spent from the start of training to this moment.|
avgR
: Average value of cumulative rewards, which is the sum of rewards in an episode.|
stdR
: Standard dev of cumulative rewards, which is the sum of rewards in an episode.|
avgS
: Average of steps in an episode.|
objC
: Objective of Critic network. Or call it loss function of critic network.|
objA
: Objective of Actor network. It is the average Q value of the critic network.################################################################################
ID Step Time | avgR stdR avgS stdS | expR objC objA etc.
tensor_action = tensor_action.argmax(dim=1)
IndexError:维度超出范围(预期在 [-1, 0] 范围内,但得到 1)
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