Reinforcement Learning
stable-baselines3
English
sb3-contrib
gymnasium
maskable-ppo
utdg
tower-defense
game-ai
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use chrisjcc/utdg-maskableppo-policy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use chrisjcc/utdg-maskableppo-policy with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="chrisjcc/utdg-maskableppo-policy", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Upload final trained model
Browse files- README.md +11 -12
- models/model_policy.zip +2 -2
README.md
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@@ -32,7 +32,7 @@ model-index:
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value: TBD
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pipeline_tag: reinforcement-learning
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metadata:
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utc_timestamp: 2025-12-
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env_name: UTDGEnv-v0
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model_file: model_policy.zip
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total_timesteps: 0
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"max_grad_norm": 1.0
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},
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"training": {
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"total_timesteps":
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"device": "auto",
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"log_interval": 2048,
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"progress_bar": true,
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"verbose": 1,
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"curriculum": {
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"enabled":
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"initial_max_steps":
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"step_increase":
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"reward_thresholds": [
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20,
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],
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"window_size": 20,
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"max_steps_cap": 10000
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---
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*Generated on 2025-12-
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value: TBD
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pipeline_tag: reinforcement-learning
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metadata:
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utc_timestamp: 2025-12-15T00:05:15.498819
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env_name: UTDGEnv-v0
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model_file: model_policy.zip
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total_timesteps: 0
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"max_grad_norm": 1.0
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},
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"training": {
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"total_timesteps": 200000,
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"device": "auto",
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"log_interval": 2048,
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"progress_bar": true,
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"verbose": 1,
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"curriculum": {
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"enabled": false,
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"initial_max_steps": 500,
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"step_increase": 1000,
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"reward_thresholds": [
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-50,
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-25,
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0,
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25,
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],
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"window_size": 20,
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"max_steps_cap": 10000
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---
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*Generated on 2025-12-15T00:05:15.498819 UTC*
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models/model_policy.zip
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:9ff9b54f638a6b1b3731ab9241d9c4a36541b729a4e6600560ad0125cbbe7469
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size 647003
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