Abstract This package provides a sampler using CMA-MAE as implemented in pyribs. CMA-MAE is a quality diversity algorithm that has demonstrated state-of-the-art performance in a variety of domains. Pyribs is a bare-bones Python library for quality diversity optimization algorithms. For a primer on CMA-MAE, quality diversity, and pyribs, we recommend referring to the series of pyribs tutorials.
For simplicity, this implementation provides a default instantiation of CMA-MAE with a GridArchive and EvolutionStrategyEmitter with improvement ranking, all wrapped up in a Scheduler.
Class or Function Names plot_grid_archive_heatmap(study: optuna.Study, ax: plt.Axes, **kwargs)
study: Optuna study with a sampler that uses pyribs. This function will plot the result archive from the sampler’s scheduler. ax: Axes on which to plot the heatmap. If None, we retrieve the current axes. **kwargs: All remaining kwargs will be passed to grid_archive_heatmap. Installation $ pip install ribs[visualize] Example A minimal example would be the following:
import matplotlib.pyplot as plt import optuna import optunahub module = optunahub.