Abstract
Random walks provide a natural framework for modeling sequential discrete decision processes. Their quantum counterparts have been proposed as potential tools for addressing such problems, particularly if suitable oracles can be constructed to encode general loss functions over decision sequences. In this talk, we discuss perspectives on how quantum random walks could be applied to decision-making and optimization problems, and outline challenges and opportunities in oracle design.