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Towards a Quantum Probability Theory of Similarity Judgments

  • James M. YearsleyEmail author
  • Emmanuel M. Pothos
  • James A. Hampton
  • Albert Barque Duran
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8951)

Abstract

We review recent progress in understanding similarity judgments in cognition by means of quantum probability theory (QP) models. We begin by outlining some features of similarity judgments that have proven difficult to model by traditional approaches. We then briefly present a model of similarity judgments based on QP, and show how it can solve many of the problems faced by traditional approaches. Finally we look at some areas where the quantum model is currently less satisfactory, and discuss some open questions and areas for further work.

Keywords

Similarity Comparison Knowledge State Quantum Model Concept Space Quantum Probability 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

E.M.P. and J.M.Y. were supported by Leverhulme Trust grant no. RPG-2013-00. Further, E.M.P. was supported by Air Force Office of Scientific Research (AFOSR), Air Force Material Command, USAF, grants no. FA 8655-13-1-3044. The US Government is authorized to reproduce and distribute reprints for Governmental purpose notwithstanding any copyright notation thereon.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • James M. Yearsley
    • 1
    Email author
  • Emmanuel M. Pothos
    • 1
  • James A. Hampton
    • 1
  • Albert Barque Duran
    • 1
  1. 1.Department of PsychologyCity University LondonLondonUK

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