Upload DQN LunarLander-v2 trained agent

DQN-MlpPolicy-LunarLander-v2.zip

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DQN-MlpPolicy-LunarLander-v2/_stable_baselines3_version

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+1.6.2

DQN-MlpPolicy-LunarLander-v2/data

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+        "bounded_above": "[False False False False False False False False]",
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+    "batch_size": 64,
+    "learning_starts": 50000,
+    "tau": 1.0,
+    "gamma": 0.999,
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+        "__doc__": "\n    Replay buffer used in off-policy algorithms like SAC/TD3.\n\n    :param buffer_size: Max number of element in the buffer\n    :param observation_space: Observation space\n    :param action_space: Action space\n    :param device: PyTorch device\n    :param n_envs: Number of parallel environments\n    :param optimize_memory_usage: Enable a memory efficient variant\n        of the replay buffer which reduces by almost a factor two the memory used,\n        at a cost of more complexity.\n        See https://github.com/DLR-RM/stable-baselines3/issues/37#issuecomment-637501195\n        and https://github.com/DLR-RM/stable-baselines3/pull/28#issuecomment-637559274\n        Cannot be used in combination with handle_timeout_termination.\n    :param handle_timeout_termination: Handle timeout termination (due to timelimit)\n        separately and treat the task as infinite horizon task.\n        https://github.com/DLR-RM/stable-baselines3/issues/284\n    ",
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+    },
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+    "target_update_interval": 625,
+    "_n_calls": 62500,
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+    },
+    "batch_norm_stats": [],
+    "batch_norm_stats_target": []
+}

DQN-MlpPolicy-LunarLander-v2/policy.optimizer.pth

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+size 44911

DQN-MlpPolicy-LunarLander-v2/policy.pth

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+size 44033

DQN-MlpPolicy-LunarLander-v2/pytorch_variables.pth

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+size 431

DQN-MlpPolicy-LunarLander-v2/system_info.txt

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+OS: Linux-5.10.133+-x86_64-with-glibc2.27 #1 SMP Fri Aug 26 08:44:51 UTC 2022
+Python: 3.8.16
+Stable-Baselines3: 1.6.2
+PyTorch: 1.13.0+cu116
+GPU Enabled: True
+Numpy: 1.21.6
+Gym: 0.21.0

README.md

@@ -0,0 +1,37 @@
+---
+library_name: stable-baselines3
+tags:
+- LunarLander-v2
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: DQN
+  results:
+  - task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: LunarLander-v2
+      type: LunarLander-v2
+    metrics:
+    - type: mean_reward
+      value: 113.79 +/- 125.13
+      name: mean_reward
+      verified: false
+---
+
+# **DQN** Agent playing **LunarLander-v2**
+This is a trained model of a **DQN** agent playing **LunarLander-v2**
+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 ...
+from huggingface_sb3 import load_from_hub
+
+...
+```

config.json

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results.json

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