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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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+ - FetchPickAndPlaceDense-v2
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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: FetchPickAndPlaceDense-v2
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+ type: FetchPickAndPlaceDense-v2
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+ metrics:
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+ - type: mean_reward
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+ value: -11.10 +/- 5.54
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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 **FetchPickAndPlaceDense-v2**
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+ This is a trained model of a **TD3** agent playing **FetchPickAndPlaceDense-v2**
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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 0x7af504baf2e0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7af504bba6c0>"}, "verbose": 0, "policy_kwargs": {"net_arch": [512, 512, 512]}, "num_timesteps": 0, "_total_timesteps": 0, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 0.0, "learning_rate": 0.001, "tensorboard_log": null, "_last_obs": null, "_last_episode_starts": null, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": 1.0, "_stats_window_size": 100, "ep_info_buffer": null, "ep_success_buffer": null, "_n_updates": 0, "observation_space": {":type:": "<class 'gymnasium.spaces.dict.Dict'>", 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