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.gitattributes

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README.md

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+---
+library_name: stable-baselines3
+tags:
+- PandaReachDense-v3
+- A2C
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: a2c-PandaReachDense-v3
+  results:
+  - task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: PandaReachDense-v3
+      type: PandaReachDense-v3
+    metrics:
+    - type: mean_reward
+      value: -0.17 +/- 0.12
+      name: mean_reward
+---
+
+# a2c-PandaReachDense-v3: **A2C** Agent playing **PandaReachDense-v3**
+
+This is a trained model of a **A2C** agent playing **PandaReachDense-v3**
+using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
+
+
+## Usage (with Stable-baselines3)
+
+TODO: Add your code
+
+
+```python
+from stable_baselines3 import ...
+
+...
+```

a2c-PandaReachDense-v3.zip

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+size 114363

replay.mp4

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results.json

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+{"mean_reward": -0.17322514443658293, "std_reward": 0.11986290127927479, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2025-11-19T19:08:38.928173"}

vec_normalize.pkl

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