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Can you share me the train logs about Figure 2 ? We can not get the similar results as shown in this figure. #3
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-----------------------------------------------Methods pred_prey_punish [test_return_mean in the log files]OW-QMIX (w=0.1) 36.8333OW-QMIX (w=0.5) 36.5000CW-QMIX (w=0.1) 37.5417 (37.6667)CW-QMIX (w=0.5) 37.5417 (36.9583)QTRAN 38.0833QPLEX 36.1667QMIX 33.6250COMA 0.0000VDN 36.7083 ( 35.7500)-----------------------------------------------VDN 37.0833 run 1VDN 36.1250 run 2VDN 36.4167 run 3QMIX 38.0417 run 1QMIX 30.2083 run 2QMIX 36.0000 run 3QPLEX 36.7083 run 1QPLEX 30.3333 run 2QPLEX 24.5417 run 3MADDPG 0MASAC 0----------------------------------------------- |
Are you annealing epsilon over 50k or over 1mil timesteps? For the results in Figure 2 of the paper, epsilon is annealed over 50k timesteps. |
CUDA_VISIBLE_DEVICES=3 nohup python3 -u src/main.py --config=vdn_smac --env-config=pred_prey_punish with epsilon_anneal_time=1000000 use_tensorboard=True > ./wjx_logs_1211/vdn_smac_pred_prey_punish_tensorboard_V2.log 2>&1 & Yes, epsilon_anneal_time=1000000 ! We can not get the similar results of vdn, qmix, and qplex in figure 2. |
Is my parameter setting wrong? |
Yeah, for Figure 2 in the paper set epsilon_anneal_time=50000 (or remove it altogether since 50k is the default). It seems that setting it as 1mil helps the performance (https://openreview.net/forum?id=Rcmk0xxIQV Appendix K.2 show similar results to yours I think). |
Thanks for your help! |
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