policy
fishing-for-best-returns
AishwaryaVathada · PyTorch
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Overview
Name
fishing-for-best-returns
Author
AishwaryaVathada
Framework
PyTorch
License
MIT
Skill type
other
Evidence level
untested
Task description
Reinforcement learning framework for long-horizon safe control in sustainable fishery management. Implements PPO, SAC, TD3, distributional RL (TQC), constrained PPO (primal-dual Lagrangian), and evolution strategies, with Optuna hyperparameter tuning and Monte Carlo policy verification under uncerta
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
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Datasets that reference this policy
0No datasets reference fishing-for-best-returns yet.