To surprise and inform

Research output: Chapter in Book/Report/Conference proceedingConference contribution


In information overload regimes, it is necessary for messages to not only provide information but also to attract attention in the first place. Bayesian surprise is an information-theoretic functional that has been experimentally shown to measure the attraction of human attention. This paper studies the limits of reliable communication under a constraint on surprise so as to limit distraction: surprise-constrained capacity. It also considers attention-seeking capacity, where the goal is to maximize both information rate and surprise to attract attention. Properties of these functions are proven. There are no nontrivial tradeoffs for surprise-constrained capacity, but an interesting tradeoff arises for attention-seeking capacity; reversing the direction of constraint does not yield essentially equivalent problems.

Original languageEnglish (US)
Title of host publication2013 IEEE International Symposium on Information Theory, ISIT 2013
Number of pages5
StatePublished - 2013
Externally publishedYes
Event2013 IEEE International Symposium on Information Theory, ISIT 2013 - Istanbul, Turkey
Duration: Jul 7 2013Jul 12 2013

Publication series

NameIEEE International Symposium on Information Theory - Proceedings
ISSN (Print)2157-8095


Other2013 IEEE International Symposium on Information Theory, ISIT 2013

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Information Systems
  • Modeling and Simulation
  • Applied Mathematics


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