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Multi measurement operation

Air Force Research Laboratory (AFRL) Autonomous Capabilities Team (ACT3) Reinforcement Learning (RL) Core.

This is a US Government Work not subject to copyright protection in the US.

The use, dissemination or disclosure of data in this file is subject to limitation or restriction. See accompanying README and LICENSE for details.

Module with implementation for multiple Observations

MultiMeasurementOperation (RewardFuncBase) ¤

Base class for any reward that is to operate on multiple measurements of some kind

Source code in corl/rewards/multi_measurement_operation.py 
class MultiMeasurementOperation(RewardFuncBase):  # pylint: disable=abstract-method
    """Base class for any reward that is to operate on multiple measurements of some kind
    """

    @property
    def get_validator(self) -> typing.Type[MultiMeasurementOperationValidator]:
        return MultiMeasurementOperationValidator

    def __init__(self, **kwargs) -> None:
        self.config: MultiMeasurementOperationValidator
        super().__init__(**kwargs)
        self._logger = logging.getLogger(self.name)
        # construct extractors
        self.extractors: typing.Dict[str, ExtractorSet] = {}
        for key, observation in self.config.observations.items():
            self.extractors[key] = observation.construct_extractors()

get_validator: Type[corl.rewards.multi_measurement_operation.MultiMeasurementOperationValidator] property readonly ¤

Returns pydantic validator associated with this class

MultiMeasurementOperationValidator (RewardFuncBaseValidator) pydantic-model ¤

observations: Dict of dicts of observation extractor arguments described in ObservationExtractorValidator

Source code in corl/rewards/multi_measurement_operation.py 
class MultiMeasurementOperationValidator(RewardFuncBaseValidator):
    """
    observations: Dict of dicts of observation extractor arguments described in ObservationExtractorValidator
    """
    observations: typing.Dict[str, ObservationExtractorValidator]