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Reinforcement Learning Generalization on Procgen 16 games (train)

27.5bigfishEDE
7.01212.33117.6522.969Jun 8, 2023

Evaluation results

MethodLinks
EDEsteps=25M, hyperparameters=tuned on bigfish2023.0627.546.927.710.69.18.210.66.692.21015.97.295.71.1
EDEsteps=25M, Hyperparameter Tuning=tuned on bigfish only2023.0627.546.927.710.69.18.210.66.692.21015.97.295.71.1
IDAACsteps=25M, hyperparameters=tuned per-game2023.0621.838.629.110.48.924.66.29.88.77.510.24.94.58.36.411.5
IDAACsteps=25M, Hyperparameter Tuning=individual games2023.0621.838.629.110.48.924.66.29.88.797.510.24.94.58.36.4
DAACsteps=25M2023.0620.13829.7108.822.55.89.88.76.9105.25.286.611.3
DAACsteps=25M2023.0620.13829.7108.822.55.89.86.91010.25.25.286.611.3
PPGsteps=25M2023.0619.949.631.111.18.916.49.59.98.710.710.25.57.49.3911.3
PPGsteps=25M2023.0619.949.631.111.18.916.49.59.98.710.710.25.57.49.3911.3
MixRegsteps=25M2023.061528.729.97.98.26.26.29.58.53.67.59.14.43.28.78.9
MixRegsteps=25M2023.061528.729.97.98.26.26.29.58.53.47.55.13.25.58.78.9
UCB-DRACsteps=25M2023.0612.833.129.38.1810.25.89.48.278.67.36.258.512
UCB-DRACsteps=25M2023.0612.833.129.38.1810.25.89.48.278.67.37.358.512
PPOsteps=25M2023.069.22928.887.36.16.79.48.34.16.95.37.15.59.111.7
PPOsteps=25M2023.069.22928.887.36.16.79.48.34.16.95.37.15.59.111.7
PLRsteps=25M2023.067.82.615.98.75.44.16.45.48.53.66.321.26.44.19.7
PLRsteps=25M2023.067.82.615.98.75.44.16.45.46.36.24.421.26.44.19.7