policy
ML-FrozenLake
AlecWaumans · PyTorch
or hover any field below to flag it
Overview
Name
ML-FrozenLake
Author
AlecWaumans
Framework
PyTorch
License
MIT
Skill type
navigation
Evidence level
untested
Task description
This project explores Reinforcement Learning on FrozenLake using two approaches: Tabular Q-Learning and Deep Q-Learning with neural networks. It compares classical vs deep RL, includes training, validation, and visualizations, and highlights reward shaping, exploration-exploitation trade-offs, and m
Spaces
Action space
other · 0-dim · 0Hz
Observation space
- type: other
Links
HuggingFace repo
null
Paper (arXiv)
null
Compatible robots
0+20 mentioned but not in catalog yetNo robots list ML-FrozenLake as compatible yet. Know of one? Flag it above.
Compatible environments
0No environments list ML-FrozenLake yet.
Datasets that reference this policy
0No datasets reference ML-FrozenLake yet.