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Offline Reinforcement Learning on puzzle-3x3-play OGBench 5 tasks v0
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87
Average Success Rate
Value Flows
-2.44
20.78
44
67.22
Oct 9, 2025
Oct 19, 2025
Oct 29, 2025
Nov 8, 2025
Nov 18, 2025
Nov 28, 2025
Dec 8, 2025
Average Success Rate
Updated 1mo ago
Evaluation Results
Method
Method
Links
Average Success Rate
Value Flows
Policy Type=Flow Policies
2025.10
87
FQL
Model Paradigm=Model-Free
2025.12
30
FQL
Policy Type=Flow Policies
2025.10
30
ReBRAC
Policy Type=Gaussian P...
2025.10
22
ReBRAC
Model Paradigm=Model-Free
2025.12
21
MOPO
Model Paradigm=Model-B...
2025.12
20
MAC
Model Paradigm=Model-B...
2025.12
20
CODAC
Policy Type=Flow Policies
2025.10
20
IFQL
Policy Type=Flow Policies
2025.10
19
IQN
Policy Type=Flow Policies
2025.10
15
FBRAC
Policy Type=Flow Policies
2025.10
14
MOBILE
Model Paradigm=Model-B...
2025.12
12
IDQL
Model Paradigm=Model-Free
2025.12
10
LEQ
Model Paradigm=Model-B...
2025.12
10
IQL
Model Paradigm=Model-Free
2025.12
9
IQL
Policy Type=Gaussian P...
2025.10
9
BC
Policy Type=Gaussian P...
2025.10
2
FMPC
Model Paradigm=Model-B...
2025.12
1
C51
Policy Type=Flow Policies
2025.10
1
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