Reinforcement Learning
ml-agents
ONNX
ML-Agents-Pyramids
Pyramids
deep-rl-course
ppo
Eval Results (legacy)
Instructions to use Learnix-AI-Lab/ppo-Pyramids with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ml-agents
How to use Learnix-AI-Lab/ppo-Pyramids with ml-agents:
mlagents-load-from-hf --repo-id="Learnix-AI-Lab/ppo-Pyramids" --local-dir="./downloads"
- Notebooks
- Google Colab
- Kaggle
File size: 650 Bytes
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tags:
- ML-Agents-Pyramids
- Pyramids
- ml-agents
- deep-rl-course
- ppo
- reinforcement-learning
library_name: ml-agents
pipeline_tag: reinforcement-learning
model-index:
- name: ppo-Pyramids
results:
- task:
name: reinforcement-learning
type: reinforcement-learning
dataset:
name: ML-Agents-Pyramids
type: ML-Agents-Pyramids
metrics:
- name: mean_reward
type: mean_reward
value: 1.95
---
# PPO Agent playing Pyramids in Unity ML-Agents
This is a trained model of a PPO agent playing ML-Agents-Pyramids using Unity ML-Agents.
- **Mean Reward**: 1.95 +/- 0.15
- **Result (mean - std)**: 1.80
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