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Source code for omni.isaac.orbit.envs.rl_task_env_cfg

# Copyright (c) 2022-2024, The ORBIT Project Developers.
# All rights reserved.
#
# SPDX-License-Identifier: BSD-3-Clause

from dataclasses import MISSING

from omni.isaac.orbit.utils import configclass

from .base_env_cfg import BaseEnvCfg
from .ui import RLTaskEnvWindow


[docs]@configclass class RLTaskEnvCfg(BaseEnvCfg): """Configuration for a reinforcement learning environment.""" # ui settings ui_window_class_type: type | None = RLTaskEnvWindow # general settings is_finite_horizon: bool = False """Whether the learning task is treated as a finite or infinite horizon problem for the agent. Defaults to False, which means the task is treated as an infinite horizon problem. This flag handles the subtleties of finite and infinite horizon tasks: * **Finite horizon**: no penalty or bootstrapping value is required by the the agent for running out of time. However, the environment still needs to terminate the episode after the time limit is reached. * **Infinite horizon**: the agent needs to bootstrap the value of the state at the end of the episode. This is done by sending a time-limit (or truncated) done signal to the agent, which triggers this bootstrapping calculation. If True, then the environment is treated as a finite horizon problem and no time-out (or truncated) done signal is sent to the agent. If False, then the environment is treated as an infinite horizon problem and a time-out (or truncated) done signal is sent to the agent. Note: The base :class:`RLTaskEnv` class does not use this flag directly. It is used by the environment wrappers to determine what type of done signal to send to the corresponding learning agent. """ episode_length_s: float = MISSING """Duration of an episode (in seconds). Based on the decimation rate and physics time step, the episode length is calculated as: .. code-block:: python episode_length_steps = ceil(episode_length_s / (decimation_rate * physics_time_step)) For example, if the decimation rate is 10, the physics time step is 0.01, and the episode length is 10 seconds, then the episode length in steps is 100. """ # environment settings rewards: object = MISSING """Reward settings. Please refer to the :class:`omni.isaac.orbit.managers.RewardManager` class for more details. """ terminations: object = MISSING """Termination settings. Please refer to the :class:`omni.isaac.orbit.managers.TerminationManager` class for more details. """ curriculum: object = MISSING """Curriculum settings. Please refer to the :class:`omni.isaac.orbit.managers.CurriculumManager` class for more details. """ commands: object = MISSING """Command settings. Please refer to the :class:`omni.isaac.orbit.managers.CommandManager` class for more details. """