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
Upload README.md with huggingface_hub
Browse files
README.md
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---
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tags:
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- ML-Agents-Pyramids
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- ml-agents
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- deep-rl-course
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- ppo
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model-index:
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- name: ppo-Pyramids
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results:
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metrics:
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- name: mean_reward
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type: mean_reward
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value: 1.
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---
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# PPO Agent playing ML-Agents
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This is a trained model of
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- **Mean Reward**: 1.
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- **Result (mean - std)**: 1.
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---
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tags:
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- ML-Agents-Pyramids
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- Pyramids
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- ml-agents
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- deep-rl-course
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- ppo
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- reinforcement-learning
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library_name: ml-agents
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pipeline_tag: reinforcement-learning
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model-index:
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- name: ppo-Pyramids
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results:
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metrics:
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- name: mean_reward
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type: mean_reward
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value: 1.95
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---
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# PPO Agent playing Pyramids in Unity ML-Agents
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This is a trained model of a PPO agent playing ML-Agents-Pyramids using Unity ML-Agents.
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- **Mean Reward**: 1.95 +/- 0.15
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- **Result (mean - std)**: 1.80
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