Expected Prediction Accuracy and the Usefulness of Contingencies

Regularities in the environment are used to decide what course of action to take and how to prepare for future events. Here we focus on the utilization of regularities for prediction and argue that the commonly considered measure of regularity - the strength of the contingency between antecedent and outcome events - does not fully capture the goodness of a regularity for predictions. We propose, instead, a new measure - the level of expected prediction accuracy (ExpPA) - which takes into account the fact that, at times, maximal prediction accuracy can be achieved by always predicting the same, most prevalent outcome, and in others, by predicting one outcome for one antecedent and another for the other. Two experiments, testing the ExpPA measure in explaining participants' behavior, found that participants are sensitive to the twin facets of ExpPA and that prediction behavior is best explained by this new measure.