policy
Rubiks-Cube-Solver
RL-Rubiks-Solver · PyTorch
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Overview
Name
Rubiks-Cube-Solver
Author
RL-Rubiks-Solver
Framework
PyTorch
License
unknown
Skill type
manipulation
Evidence level
untested
Task description
This project implements and compares multiple model-free reinforcement learning algorithms — including Q-Learning, REINFORCE, and Proximal Policy Optimization (PPO) — to train agents capable of solving a 2x2x2 Rubik's Cube environment.
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
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