Reinforcement Learning
ml-agents
ONNX
Pyramids
unity-ml-agents
deep-reinforcement-learning
ML-Agents-Pyramids
Eval Results (legacy)
Instructions to use saisowrya/ppo-Pyramids with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ml-agents
How to use saisowrya/ppo-Pyramids with ml-agents:
mlagents-load-from-hf --repo-id="saisowrya/ppo-Pyramids" --local-dir="./downloads"
- Notebooks
- Google Colab
- Kaggle
File size: 709 Bytes
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tags:
- Pyramids
- ml-agents
- unity-ml-agents
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-Pyramids
model-index:
- name: ppo-Pyramids
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: ML-Agents-Pyramids
type: ML-Agents-Pyramids
metrics:
- type: mean_reward
value: 1.85 +/- 0.15
name: mean_reward
---
# **PPO** Agent playing **Pyramids**
This is a trained model of a **PPO** agent playing **Pyramids** using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
## Evaluation Results
- **Mean Reward**: 1.85 +/- 0.15 (Target: >= -100)
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