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Reinforcement Learning Surrogate Modeling on Pendulum (P) (test)
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95
Reward Ratio
Cubist
58.6
68.05
77.5
86.95
Jul 8, 2026
Reward Ratio
Test MSE
Test MSE (x10^-3)
Updated 17d ago
Evaluation Results
Method
Method
Links
Reward Ratio
Test MSE
Test MSE (x10^-3)
Cubist
MNR=30, Model Size=250±1
2026.07
95
0.021
-
Decision Tree
MD=10, Model Size=1625±40
2026.07
93
0.037
-
ORCAID
MD=3, Model Size=59±2
2026.07
92
0.024
-
Decision Tree
MD=8, Model Size=848±44
2026.07
85
-
7
ORCAID
MD=2, Model Size=19±1
2026.07
84
-
15
Cubist
MNR=4, Model Size=27±0
2026.07
82
-
8
RuleFit
MNR=14, Model Size=61±7
2026.07
78
-
13
RuleFit
MNR=10, Model Size=43±4
2026.07
60
0.104
-
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