DICG
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Zero win rate in SMAC scenario
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?
How many environment steps did your experiments take?
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.