MURAL - Maynooth University Research Archive Library

    Seeing Patterns in Randomness: A Computational Model of Surprise.

    Maguire, Phil and Moser, Philippe and Maguire, Rebecca and Keane, Mark T. (2019) Seeing Patterns in Randomness: A Computational Model of Surprise. Topics in Cognitive Science, 11. pp. 103-118. ISSN 1756-8757

    Download (199kB) | Preview

    Share your research

    Twitter Facebook LinkedIn GooglePlus Email more...

    Add this article to your Mendeley library


    While seemingly a ubiquitous cognitive process, the precise definition and function of surprise remains elusive. Surprise is often conceptualized as being related to improbability or to contrasts with higher probability expectations. In contrast to this probabilistic view, we argue that surprising observations are those that undermine an existing model, implying an alternative causal origin. Surprises are not merely improbable events; instead, they indicate a breakdown in the model being used to quantify probability. We suggest that the heuristic people rely on to detect such anomalous events is randomness deficiency. Specifically, people experience surprise when they identify patterns where their model implies there should only be random noise. Using algorithmic information theory, we present a novel computational theory which formalizes this notion of surprise as randomness deficiency. We also present empirical evidence that people respond to randomness deficiency in their environment and use it to adjust their beliefs about the causal origins of events. The connection between this pattern-detection view of surprise and the literature on learning and interestingness is discussed.

    Item Type: Article
    Additional Information: Cite as: Maguire, P., Moser, P., Maguire, R. and Keane, M.T. (2019), Seeing Patterns in Randomness: A Computational Model of Surprise. Top Cogn Sci, 11: 103-118.
    Keywords: Surprise; Randomness deficiency; Algorithmic information theory; Bayesian reasoning;Stochastic model; Representational updating; Interestingness; Data compression;
    Academic Unit: Faculty of Science and Engineering > Psychology
    Faculty of Science and Engineering > Computer Science
    Item ID: 13585
    Identification Number:
    Depositing User: Phil Maguire
    Date Deposited: 18 Nov 2020 17:01
    Journal or Publication Title: Topics in Cognitive Science
    Publisher: Wiley Online Library
    Refereed: Yes
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

    Repository Staff Only(login required)

    View Item Item control page


    Downloads per month over past year

    Origin of downloads