unreal.LearningAgentsImitationTrainer

class unreal.LearningAgentsImitationTrainer(outer: Object | None = None, name: Name | str = 'None')

Bases: LearningAgentsManagerListener

The ULearningAgentsImitationTrainer enable imitation learning, i.e. learning from human/AI demonstrations. Imitation training is typically much faster than reinforcement learning, but requires gathering large amounts of data in order to generalize. This can be used to initialize a reinforcement learning policy to speed up initial exploration. see: ULearningAgentsInteractor to understand how observations and actions work. see: ULearningAgentsController to understand how we can manually perform actions via a human or AI. see: ULearningAgentsRecorder to understand how to make new recordings.

C++ Source:

  • Plugin: LearningAgents

  • Module: LearningAgentsTraining

  • File: LearningAgentsImitationTrainer.h

Editor Properties: (see get_editor_property/set_editor_property)

  • has_training_failed (bool): [Read-Only] True if trainer encountered an unrecoverable error during training (e.g. the trainer process timed out). Otherwise, false. This exists mainly to keep the editor from locking up if something goes wrong during training.

  • interactor (LearningAgentsInteractor): [Read-Only] The interactor being trained.

  • is_setup (bool): [Read-Only] True if this object has been setup. Otherwise, false.

  • is_training (bool): [Read-Only] True if training is currently in-progress. Otherwise, false.

  • manager (LearningAgentsManager): [Read-Only] The manager this object is associated with.

  • policy (LearningAgentsPolicy): [Read-Only] The policy being trained.

  • visual_logger_objects (Map[Name, LearningAgentsVisualLoggerObject]): [Read-Only] The visual logger objects associated with this listener.

begin_training(recording, imitation_trainer_settings=[], imitation_trainer_training_settings=[], imitation_trainer_path_settings=[]) → None

Begins the training process with the provided settings.

Parameters:
end_training() → None

Stops the training process.

has_training_failed() → bool

Returns true if the trainer has failed to communicate with the external training process. This can be used in combination with RunTraining to avoid filling the logs with errors.

Returns:

True if the training has failed. Otherwise, false.

Return type:

bool

is_training() → bool

Returns true if the trainer is currently training; Otherwise, false.

Return type:

bool

iterate_training() → None

Iterates the training process and gets the updated policy network.

classmethod make_imitation_trainer(manager, interactor, policy, class_=None) → LearningAgentsImitationTrainer

Constructs the imitation trainer and runs the setup functions.

Parameters:
Return type:

LearningAgentsImitationTrainer

run_training(recording, imitation_trainer_settings=[], imitation_trainer_training_settings=[], imitation_trainer_path_settings=[]) → None

Convenience function that runs a basic training loop. If training has not been started, it will start it. On each following call to this function, it will call IterateTraining.

Parameters: