policy
PPO_PyBullet_Minitaur
EricChen0104 · PyTorch
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Overview
Name
PPO_PyBullet_Minitaur
Author
EricChen0104
Framework
PyTorch
License
MIT
Skill type
other
Evidence level
untested
Task description
This project implements a Proximal Policy Optimization (PPO) reinforcement learning agent to train the Minitaur robot to walk in the MinitaurBulletEnv-v0 environment using PyBullet. The agent uses a multilayer perceptron (MLP) to model the policy and value networks and learns to control the robot in
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 PPO_PyBullet_Minitaur yet.
Datasets that reference this policy
0No datasets reference PPO_PyBullet_Minitaur yet.