Abstract MAPCMASampler provides an implementation of the MAP-IGO (maximum a posteriori information geometric optimization) framework, which extends the CMA-ES rank-one-update. This sampler adds momentum-based updates to the standard CMA-ES, following the MAP-IGO algorithm.
Class or Function Names MAPCMASampler(mean: dict[str, Any] | None = None, sigma0: float | None = None, seed: int | None = None, popsize: int | None = None, cov: np.ndarray | None = None, momentum_r: float | None = None, search_space: dict[str, BaseDistribution] | None = None, independent_sampler: BaseSampler | None = None) mean: Initial mean of MAPCMA.