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Copy file name to clipboardExpand all lines: docs/custom/custom_task.rst
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@@ -16,7 +16,7 @@ To define your own task, you need to inherit from :py:class:`Task<panda_gym.envs
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- ``reset()``: how the task is reset; you must define `self.goal` in this function
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- ``get_obs()``: returns the observation
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- ``get_achieved_goal()``: returns the achieved goal
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- ``is_success(achieved_goal, desired_goal, info)``: returns whether the task is successfull
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- ``is_success(achieved_goal, desired_goal, info)``: returns whether the task is successful
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- ``compute_reward(achieved_goal, desired_goal, info)``: returns the reward
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For the purpose of the example, let's consider here a very simple task, consisting in moving a cube toward a target position. The goal position is sampled within a volume of 10 m x 10 m x 10 m.
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Copy file name to clipboardExpand all lines: docs/usage/train_with_sb3.rst
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-----------------------------------
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`RL Baselines3 Zoo <https://stable-baselines3.readthedocs.io/en/master/guide/rl_zoo.html>`_ is the training framework associated with SB3.
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It provides scripts for training, evaluating agents, setting hyperparameters, plotting results and recording video. It also contains already optimized hypermeters, including for some ``panda-gym`` environments.
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It provides scripts for training, evaluating agents, setting hyperparameters, plotting results and recording video. It also contains already optimized hyperparameters, including for some ``panda-gym`` environments.
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.. warning::
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The current version of RL Baselines3 Zoo provides hyperparameters for version 1 of ``panda-gym``, but not for version 2. Before training with RL Baselines3 Zoo, you will have to set your own hyperparameters by editing ``hyperparameters/<ALGO>.yml``. For more information, please read the `README of RL Baselines3 Zoo <https://github.com/DLR-RM/rl-baselines3-zoo#readme>`_.
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