Research on surprise relevant to the cognitive-evolutionary model of surprise proposed by Meyer, Reisenzein, and Schützwohl is reviewed. The majority of the assumptions of the model are found empirically supported. Surprise is evoked by unexpected events and its intensity is determined by the degree if schema-discrepancy, whereas the novelty and the valence of the eliciting events probably do not have an independent effect. Unexpected events cause an automatic interruption of ongoing mental processes that is followed by an attentional shift and (...) attentional binding to the events, which is often followed by causal and other event analysis processes and by schema revision. The facial expression of surprise postulated by evolutionary emotion psychologists has been found to occur rarely in surprise, for as yet unknown reasons. A physiological orienting response marked by skin conductance increase, heart rate deceleration, and pupil dilation has been observed to occur regularly in the standard version of the repetition-change paradigm of surprise induction, but the specificity of these reactions as indicators of surprise is controversial. There is indirect evidence for the assumption that the feeling of surprise consists of the direct awareness of the schema-discrepancy signal, but this feeling, or at least the self-report of surprise, is also influenced by experienced interference. In contrast, facial feedback probably does contribute substantially to the feeling of surprise and the evidence for the hypothesis that surprise is affected by the difficulty of explaining an unexpected event is, in our view, inconclusive. Regardless of how the surprise feeling is constituted, there is evidence that it has both motivational and informational effects. Finally, the prediction failure implied by unexpected events sometimes causes a negative feeling, but there is no convincing evidence that this is always the case, and we argue that even if it were so, this would not be a sufficient reason for regarding this feeling as a component, rather than as an effect of surprise. (shrink)

In a series of three behavioral experiments, we found a systematic distortion of probability judgments concerning elementary visual stimuli. Participants were briefly shown a set of figures that had two features (e.g., a geometric shape and a color) with two possible values each (e.g., triangle or circle and black or white). A figure was then drawn, and participants were informed about the value of one of its features (e.g., that the figure was a “circle”) and had to predict the value (...) of the other feature (e.g., whether the figure was “black” or “white”). We repeated this procedure for various sets of figures and, by varying the statistical association between features in the sets, we manipulated the probability of a feature given the evidence of another (e.g., the posterior probability of hypothesis “black” given the evidence “circle”) as well as the support provided by a feature to another (e.g., the impact, or confirmation, of evidence “circle” on the hypothesis “black”). Results indicated that participants’ judgments were deeply affected by impact, although they only should have depended on the probability distributions over the features, and that the dissociation between evidential impact and posterior probability increased the number of errors. The implications of these findings for lower and higher level cognitive models are discussed. (shrink)

This special issue presents developments in research on the cognitive mechanisms and consequences of surprise. Amidst much progress, surprise research has often been siloed, so, as editors, we have sought to juxtapose insights, theories, and findings, to support cross‐fertilization in future research. The present paper sets the stage by presenting a historical summary, highlighting contrasts in definitions, and tracing major threads running through this issue and the larger surprise literature.

In this article, we present a new logical framework to think about surprise. This research does not just aim to better understand, model and predict human behaviour, but also attempts to provide tools for implementing artificial agents. Moreover, these artificial agents should then also be able to reap the same epistemic benefits from surprise as humans do. We start by discussing the dominant literature regarding propositional surprise and explore its shortcomings. These shortcomings are of both an empirical and a conceptual (...) nature. Next, we propose a philosophical solution to the problems that ail these systems, based on the notion of issue of epistemic interest. Finally, we give a formal framework to think about surprise. More specifically, we develop a probabilistic dynamic epistemic logic that succeeds at formalizing the relevant philosophical concepts. This will be done through an issue management system grounded in topology. As an added bonus, the additional expressive power allows us to capture a richer variety of scenarios, and it also enables a more careful analysis of said scenarios. (shrink)