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README.md ADDED
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+ ---
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+ library_name: stable-baselines3
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+ tags:
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+ - PandaPickAndPlaceDense-v3
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+ - deep-reinforcement-learning
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+ - reinforcement-learning
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+ - stable-baselines3
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+ model-index:
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+ - name: TD3
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+ results:
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+ - task:
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+ type: reinforcement-learning
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+ name: reinforcement-learning
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+ dataset:
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+ name: PandaPickAndPlaceDense-v3
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+ type: PandaPickAndPlaceDense-v3
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+ metrics:
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+ - type: mean_reward
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+ value: -10.67 +/- 3.74
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+ name: mean_reward
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+ verified: false
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+ ---
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+
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+ # **TD3** Agent playing **PandaPickAndPlaceDense-v3**
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+ This is a trained model of a **TD3** agent playing **PandaPickAndPlaceDense-v3**
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+ using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
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+
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+ ## Usage (with Stable-baselines3)
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+ TODO: Add your code
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+
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+
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+ ```python
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+ from stable_baselines3 import ...
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+ from huggingface_sb3 import load_from_hub
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+
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+ ...
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+ ```
config.json ADDED
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rate, to pass to the optimizer\n :param n_critics: Number of critic networks to create.\n :param share_features_extractor: Whether to share or not the features extractor\n between the actor and the critic (this saves computation time)\n ", "__init__": "<function MultiInputPolicy.__init__ at 0x79f7ba9d32e0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x79f7ba9d5bc0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1000000, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1719148534956247250, "learning_rate": 0.001, "tensorboard_log": null, "_last_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": 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+ - OS: Linux-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Apr 28 14:29:16 UTC 2024
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+ - Python: 3.10.12
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+ - Stable-Baselines3: 2.3.2
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+ - PyTorch: 2.3.0+cu121
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+ - GPU Enabled: False
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+ - Numpy: 1.25.2
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+ - Cloudpickle: 2.2.1
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+ - Gymnasium: 0.29.1
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+ - OpenAI Gym: 0.25.2
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