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Reward func base

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.

Reward Functor Base Module

RewardFuncBase (EnvFuncBase) ¤

The base implementation for reward functors

Source code in corl/rewards/reward_func_base.py 
class RewardFuncBase(EnvFuncBase):
    """The base implementation for reward functors
    """

    def __init__(self, **kwargs):
        self.config: RewardFuncBaseValidator = self.get_validator(**kwargs)

    @property
    def get_validator(self) -> typing.Type[RewardFuncBaseValidator]:
        """Returns pydantic validator associated with this class
        """
        return RewardFuncBaseValidator

    @abc.abstractmethod
    def __call__(
        self,
        observation: OrderedDict,
        action,
        next_observation: OrderedDict,
        state: StateDict,
        next_state: StateDict,
        observation_space: StateDict,
        observation_units: StateDict,
    ) -> RewardDict:
        ...

    def post_process_trajectory(self, agent_id, state, batch, episode, policy):  # pylint: disable=unused-argument,no-self-use
        """Allows the user to modify the trajectory of the episode
        in the batch collected during an rllib callback. WARNING: This function is dangerous
        you can completly destroy training using this
        Use it only as a last resort
        """
        ...

    @property
    def name(self) -> str:
        """ gets the name fo the functor

        Returns
        -------
        str
            The name of the functor
        """
        return type(self).__name__ if self.config.name is None else self.config.name

get_validator: Type[corl.rewards.reward_func_base.RewardFuncBaseValidator] property readonly ¤

Returns pydantic validator associated with this class

name: str property readonly ¤

gets the name fo the functor

Returns¤

str The name of the functor

post_process_trajectory(self, agent_id, state, batch, episode, policy) ¤

Allows the user to modify the trajectory of the episode in the batch collected during an rllib callback. WARNING: This function is dangerous you can completly destroy training using this Use it only as a last resort

Source code in corl/rewards/reward_func_base.py 
def post_process_trajectory(self, agent_id, state, batch, episode, policy):  # pylint: disable=unused-argument,no-self-use
    """Allows the user to modify the trajectory of the episode
    in the batch collected during an rllib callback. WARNING: This function is dangerous
    you can completly destroy training using this
    Use it only as a last resort
    """
    ...

RewardFuncBaseValidator (BaseModel) pydantic-model ¤

name: Name of reward functor agent_name: Name of agent the reward functor belongs to

Source code in corl/rewards/reward_func_base.py 
class RewardFuncBaseValidator(BaseModel):
    """
    name: Name of reward functor
    agent_name: Name of agent the reward functor belongs to
    """
    name: typing.Optional[str]
    agent_name: str