What comes to mind? Samples from relevance-based feature spaces

Recent work in judgment and decision making has focused on which actions people consider when solving open-ended problems and found that the actions that come to mind tend to have particular features, such as having a high historical value. Here, we pursue the idea that the process of generating actions for decision-making tasks may actually reflect more general mechanisms for generating kinds of things. We provide evidence that what comes to mind may simply be a reflection of participants sampling from the most relevant part of the representational space they use to encode the type of thing they are generating. In this paper, we (1) introduce an approach for empirically describing a category in terms of the features that people use to represent category members, and for locating category members within that feature space, (2) show that certain locations in a category's feature space predict an item's likelihood of coming to mind, (3) introduce an approach for understanding the relevance of various features to people's representations of category members, and (4) show that features which are most involved in people's representations of category members are also predictors of what comes to mind within a category. We close by proposing that features that are most relevant to our representations of category members and predict coming to mind are those for which it has been historically useful to have information about during past experiences with the category in question.