Reinforcement Learning
ml-agents
ONNX
ML-Agents-Pyramids
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use LalithKumarRaju/MLAgents-Pyramids with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ml-agents
How to use LalithKumarRaju/MLAgents-Pyramids with ml-agents:
mlagents-load-from-hf --repo-id="LalithKumarRaju/MLAgents-Pyramids" --local-dir="./downloads"
- Notebooks
- Google Colab
- Kaggle
PPO Agent playing ML-Agents-Pyramids
This model was trained as part of the 🤗 Hugging Face Deep Reinforcement Learning Course by Lalith Kumar Raju (LalithKumarRaju).
Evaluation Results
- Environment:
ML-Agents-Pyramids - Mean Reward:
1.80 +/- 0.20 - Baseline Requirement: $\ge -100$
Description
This repository contains the trained weights, configuration files, and evaluation metadata for Unit 5 P2.
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Evaluation results
- mean_reward on ML-Agents-Pyramidsself-reported1.80 +/- 0.20