  Many real-world engineering problems rely on human preferences to guide their
design and optimization. We present PrefOpt, an open source package to simplify
sequential optimization tasks that incorporate human preference feedback. Our
approach extends an existing latent variable model for binary preferences to
allow for observations of equivalent preference from users.
