Source code for alf_tools.optimizer.acquisition_functions.greedy

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from alf_core import AcquisitionFunction, Candidate, LabelledCandidates, State




class Greedy(AcquisitionFunction):
    """Greedy acquisition function.

    The Greedy acquisition value is given by: Greedy = μ, where μ is the mean prediction.
    Higher Greedy values indicate more promising candidates.
    This is a maximising acquisition function.
    """

    def __call__(self, search_candidates: list[Candidate], state: State) -> LabelledCandidates:
        """Compute greedy acquisition values for unlabelled candidates.

        Args:
            search_candidates: List of unlabelled candidates to score.
            state: The task state containing the current datasets and surrogate model.

        Returns:
            LabelledCandidates with Greedy acquisition values.
        """
        predictions = state.surrogate.predict(search_candidates)
        acquisition_values = predictions.means
        return LabelledCandidates(candidates=search_candidates, labels=acquisition_values)