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License: MIT License
Thanks for preparing the whole training script and the JAX environment.
I have minor suggestion to improve the target for the value network.
When using sequential halving, the search does exploration to find the best action.
The root value is then possibly underestimated, because the average value includes the values of the explored actions.
mctx_learning_demo/basic_tree_search.py
Line 189 in e79a655
A better target for the value network would be the Q-value of the selected action:
search_value = policy_output.search_tree.qvalues(policy_output.action)
Is there any visualization of the task like I can use the trained model?
I install Haiku through this command:
pip install git+https://github.com/deepmind/dm-haiku
But I got this error:
Traceback (most recent call last):
File "basic_tree_search.py", line 2, in <module>
import haiku as hk
File "/home/percyp/anaconda3/envs/isaac/lib/python3.8/site-packages/haiku/__init__.py", line 19, in <module>
from haiku import data_structures
File "/home/percyp/anaconda3/envs/isaac/lib/python3.8/site-packages/haiku/data_structures.py", line 18, in <module>
from haiku._src.data_structures import to_haiku_dict
File "/home/percyp/anaconda3/envs/isaac/lib/python3.8/site-packages/haiku/_src/data_structures.py", line 30, in <module>
from haiku._src import utils
File "/home/percyp/anaconda3/envs/isaac/lib/python3.8/site-packages/haiku/_src/utils.py", line 42, in <module>
def auto_repr(cls: type[Any], *args, **kwargs) -> str:
TypeError: 'type' object is not subscriptable
Am I installing from the wrong place? Could you help me solve this problem?
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