Seeing Patterns in Randomness: A Computational Model of Surprise

Topics in Cognitive Science 11 (1):103-118 (2019)
  Copy   BIBTEX

Abstract

Much research has linked surprise to violation of expectations, but it has been less clear how one can be surprised when one has no particular expectation. This paper discusses a computational theory based on Algorithmic Information Theory, which can account for surprises in which one initially expects randomness but then notices a pattern in stimuli. The authors present evidence that a “randomness deficiency” heuristic leads to surprise in such cases.

Other Versions

No versions found

Links

PhilArchive



    Upload a copy of this work     Papers currently archived: 101,505

External links

Setup an account with your affiliations in order to access resources via your University's proxy server

Through your library

Analytics

Added to PP
2018-05-18

Downloads
56 (#385,917)

6 months
6 (#869,904)

Historical graph of downloads
How can I increase my downloads?