Comments (3)
Hello, thank you very much for your interest.
Please note that the SampledEfficientZero
algorithm implemented in LightZero currently supports environments with fixed discrete action spaces, such as Atari, as well as environments with continuous action spaces like MuJoCo.
We haven't yet
adapted the algorithm for board game environments with variable action spaces
. We expect to make these adjustments around the end of October.
However, if you currently have a need for this functionality, we warmly welcome your participation and contribution. We can discuss and address any potential adaptation issues together in this issue thread. We look forward to your contributions, and deeply appreciate your support.
Wishing you all the best.
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To give some context and tried solutions to the problem:
- Limiting the amount of sampled actions inside the aforementioned expand function breaks the homogeneity of child_sampled_actions_segment inside the GameSegment and child_sampled_actions_batch inside the _learn_forward in SampledEfficientzero Policy
- Accurately limiting reassigning of legal_actions inside the aforementioned expand function to block the expanding of illegal action nodes seems to work, but my experiments right now are inconclusive, it can be a good enough temporary solution if you need the functionality right now.
from lightzero.
Looks like Commit e32e495e solved this issue.
from lightzero.
Related Issues (20)
- Pip install failing on linux HOT 1
- No module named 'lzero.worker.gumbel_muzero_collector' HOT 1
- gumbel_muzero error HOT 1
- Installation fails on MacBook M1 Pro HOT 6
- alphazero MCTS not working: cannot import mcts_alphazero HOT 4
- Confusion between "battle_mode" and "mcts_mode" HOT 2
- AttributeError: 'EasyDict' object has no attribute 'replay_path_gif' HOT 2
- Is there a missing .gitmodules file? HOT 2
- A typo in the comment of _ucb_score HOT 2
- [action_mask error] HOT 6
- Sampled MuZero and Sampled EfficientZero HOT 3
- Default lunar lander settings result in RuntimeError during model evaluation HOT 2
- Bipedal continuous discretized sampled efficientzero config error HOT 2
- Tensors on different devices when using GPU (SampledEfficientZeroPolicy) HOT 2
- gomoku muzero self play train problem HOT 1
- `SampledEfficientZeroModel` does not pass `lstm_hidden_size` through `DynamicsNetwork` HOT 2
- Potentially mishandled continuous action space shape HOT 4
- Question about gumbel_scale and dirichlet noise in Gumbel MuZero HOT 1
- Does `downsample = True` lead to masking input data? HOT 1
- JAX support HOT 3
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