Proceedings of the Annual Meeting of the Cognitive Science Society

The criteria for guiding endogenous attention are largely unknown. A prominent view is that humans preferentiallyengage with information of intermediate complexity, and minimize engagement with too simple or too complex events.Here, we operationalize the notions of engagement and complexity to test this hypothesis. We asked participants toengage with differentially complex sequences of symbols shown one-by-one and disengage when they 1) could predictthe next element of the sequence, or 2) felt the sequence was unpredictable. We define sequence complexity as a functionof the probability of obtaining that sequence from a particular Hidden Markov Model. This extends previous measuresof complexity to respect sequential structure and closely relates to the algorithmic complexity of sequence-generatingprograms. We construct different measures using this operationalization of sequence complexity to predict the probabilityof disengagement at each event. We assess under which definitions intermediate complexity is preferred.