policy
offline-DRL
MK25BM · PyTorch
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Overview
Name
offline-DRL
Author
MK25BM
Framework
PyTorch
License
unknown
Skill type
other
Evidence level
untested
Task description
The provided Python code implements a comprehensive offline reinforcement learning (RL) pipeline, focusing on a simulated Type 1 Diabetes (T1D) environment. The pipeline covers environment setup, data collection, dataset management, offline RL algorithm configuration, training, evaluation, and model
Spaces
Action space
other · 0-dim · 0Hz
Observation space
- type: other
Links
HuggingFace repo
null
Paper (arXiv)
null
Compatible robots
3+17 mentioned but not in catalog yetCompatible environments
0No environments list offline-DRL yet.
Datasets that reference this policy
0No datasets reference offline-DRL yet.