Comments (3)
Yep, the exploration is purely via temperature in the code. Should be fairly easy to incorporate Dirichlet noise. It was a little unclear whether they use the noise in the evaluation stage.
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@pathway there is sample implementation of Dirichlet noise in the following repo.
The noise is used in self-play only.
from alpha-zero-general.
Btw how do you achieve exploration currently, is it purely via temperature?
Different exploration strategies are quite interesting.
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Related Issues (20)
- mainTafl.py does not work for me
- Initial exploration values in MCTS HOT 1
- Single Player Game HOT 1
- Issue in loss in pytorch version? HOT 2
- Throw except 'TypeError: build() missing 1 required keyword-only argument: 'roles'' when I run example demo HOT 1
- Not pure RL HOT 1
- ZeroDivisionError: float division by zero HOT 7
- A fast, parallel and batched fork of this repo HOT 1
- mcts is reset after every episode? HOT 1
- self play is exceptionally slow on GPU HOT 1
- Chess implementation? HOT 6
- Request: moving pretrained_models to git submodule
- Request: publishing package(s) to PyPI
- MCTS simulation
- Using while loop in the MCTS search function instead of recursion
- google colab err
- Actionspace 1 to many HOT 3
- Game with player getting double turns / moves HOT 5
- mini-othello not trained right?
- Nit: Chess requires more than the state of the board.
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