Non-Stationary Reinforcement Learning on Toy Environments Non-Stationary benchmark leaderboard · SOTA2 Research

Non-Stationary Reinforcement Learning on Toy Environments Non-Stationary

1.13nAUC (Steady)SAC+AES

Evaluation Results

Method	Links
SAC+AES2026.01		1.13	0.88	0.94	0.94	0.97	0	0.22	0.17	0.17	0.14
SAC2026.01		1	0.72	0.8	0.81	0.73	0	0.28	0.2	0.19	0.27
SQL+AES2026.01		0.98	0.9	0.94	0.93	0.91	0	0.08	0.04	0.05	0.07
MEow+AES2026.01		0.97	1.03	1.02	1.01	0.83	0	-0.06	-0.05	-0.04	0.14
SQL2026.01		0.9	0.75	0.82	0.77	0.68	0	0.17	0.09	0.14	0.24
MEow2026.01		0.9	0.79	0.87	0.86	0.77	0	0.12	0.03	0.04	0.14
PPO2026.01		0.89	0.75	0.79	0.71	0.67	0	0.16	0.11	0.2	0.25
PPO+AES2026.01		0.89	0.92	0.92	0.89	0.79	0	-0.03	-0.03	0	0.11