Another target area for improvement is the robustness of the surrogate building process; roughly 50% of the optimization terminate early, as issues with automatic relevance determination (ARD) cause surrogates to sacrifice accuracy to the point where they can no longer find an improved solution. While all optimization runs still led to improved parameters overall, this suggests that parameter quality could be higher with improved surrogates. Potential solutions include different choices of GP covariance kernel, or implementing alternative methods of ARD.