Comments (1)
There is no support for continuous action spaces currently, but there is no reason why it wouldn't be possible to augment the code to work with continuous action spaces. Each option essentially works as a policy gradient so you would have to change the following lines
option-critic-pytorch/option_critic.py
Lines 143 to 144 in 102436c
where num_actions should be the dimensionality of the mean and diagonal covariance. Also change
option-critic-pytorch/option_critic.py
Line 172 in 102436c
to be a Gaussian distribution.
from option-critic-pytorch.
Related Issues (9)
- Termination prob calculated over current state instead of the next state HOT 2
- Why not clean replay buffer after each episode for on-policy policy gradient update? HOT 4
- Actor called with a single sample 1/batchsize proportion of the time. HOT 1
- Should "--num-options 4" be added?
- Q[option] should also have a detach() when calculating ac_loss HOT 2
- Biased gradients HOT 2
- Got an error of inplace operation while running the code HOT 2
- loss.backward error HOT 4
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from option-critic-pytorch.