gym/envs/mujoco/half_cheetah_v3.py [36:60]:
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            forward_reward_weight,
            ctrl_cost_weight,
            reset_noise_scale,
            exclude_current_positions_from_observation,
            **kwargs
        )

        self._forward_reward_weight = forward_reward_weight

        self._ctrl_cost_weight = ctrl_cost_weight

        self._reset_noise_scale = reset_noise_scale

        self._exclude_current_positions_from_observation = (
            exclude_current_positions_from_observation
        )

        if exclude_current_positions_from_observation:
            observation_space = Box(
                low=-np.inf, high=np.inf, shape=(17,), dtype=np.float64
            )
        else:
            observation_space = Box(
                low=-np.inf, high=np.inf, shape=(18,), dtype=np.float64
            )
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gym/envs/mujoco/half_cheetah_v4.py [154:178]:
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            forward_reward_weight,
            ctrl_cost_weight,
            reset_noise_scale,
            exclude_current_positions_from_observation,
            **kwargs
        )

        self._forward_reward_weight = forward_reward_weight

        self._ctrl_cost_weight = ctrl_cost_weight

        self._reset_noise_scale = reset_noise_scale

        self._exclude_current_positions_from_observation = (
            exclude_current_positions_from_observation
        )

        if exclude_current_positions_from_observation:
            observation_space = Box(
                low=-np.inf, high=np.inf, shape=(17,), dtype=np.float64
            )
        else:
            observation_space = Box(
                low=-np.inf, high=np.inf, shape=(18,), dtype=np.float64
            )
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