UTILIZING PRIOR KNOWLEDGE IN ROBUST OPTIMAL EXPERIMENT DESIGN

Abstract In this paper we propose a new approach to robust optimal experiment design. The key departure from earlier work is that we specifically account for the fact that, prior to the experiment, we possess only partial knowledge of the system. We also give a detailed analysis of the solution for a simple case and propose a concave optimization algorithm that can be applied more generally.