Low Dimensional Representations in Multi-Cue Judgement

The study of multi-cue judgment investigates how decision makers integrate cues to predict the value of a criterion variable. We consider a multi-cue judgment task in which decision makers have prior knowledge of inter-cue relationships but are ignorant of how the cues correlate with the criterion. In this setting, a naive judgment strategy prescribes an equal weight for each cue. However, we find that many participants appear to use a weighting scheme based on a low-dimensional representation of the cue space. The use of such a representation is consistent with core insights in semantic memory research and has important optimality properties concerning judgment accuracy.