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Hello, thanks for your elegant code.
When I directly run:
python dicg_ce_smac_runner.py --map 3s_vs_5z
python dicg_ce_smac_runner.py --map 6h_vs_8z
the win rate is always zero.
When I directly run:
python dicg_ce_smac_runner.py --map 8m_vs_9m
the win rate is lower than 0.1,
which are very different from the results reported in the paper.
Can you give me a hand?
The text was updated successfully, but these errors were encountered:
More than 800 steps shown in the tensorboard, where I find the EvalAvgReturn is converge to 10.8.
By the way, dicg_de_smac_runner.py --map 8m_vs_9m can achieve 0.9 win rate in the same environment step.
Hello, thanks for your elegant code.
When I directly run:
python dicg_ce_smac_runner.py --map 3s_vs_5z
python dicg_ce_smac_runner.py --map 6h_vs_8z
the win rate is always zero.
When I directly run:
python dicg_ce_smac_runner.py --map 8m_vs_9m
the win rate is lower than 0.1,
which are very different from the results reported in the paper.
Can you give me a hand?
The text was updated successfully, but these errors were encountered: