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5 results

Quantum Models of Cognition and Decision
  • Principles and Applications
  • 2nd edition
  • Jerome R. Busemeyer, Peter D. Bruza
  • Published online:
    14 November 2024
    Print publication:
    21 November 2024
  • Quantum Models of Cognition and Decision, Second Edition presents a fully updated and expanded version of this innovative and path-breaking text. It offers an accessible introduction to the intersection of quantum theory and cognitive science, covering new insights, modelling techniques, and applications for understanding human cognition and decision making. In it, Busemeyer and Bruza delve into such topics as the non-commutative nature of judgments, quantum interference as a general principle governing human decision making, contextuality in modelling human cognition, and thought-provoking speculation about what a quantum approach to cognition might reveal about the ultimate nature of the human mind. Additions include new material on measurement, open systems, and applications to computer science. Requiring no prior background in quantum physics, this book comes complete with a tutorial and fully worked-out applications in important areas of cognition and decision.

  • 2 - Quantum probability approach to spectral analysis of growing graphs

  • Edited by R. A. Bailey, University of St Andrews, Scotland, Peter J. Cameron, University of St Andrews, Scotland, Yaokun Wu, Shanghai Jiao Tong University, China
  • Book:
    Groups and Graphs, Designs and Dynamics
    Published online:
    11 May 2024
    Print publication:
    30 May 2024, pp 87-175

  • Summary

    These lecture notes provide quantum probabilistic concepts and methods for spectral analysis of graphs, in particular, for the study of asymptotic behavior of the spectral distributions of growing graphs. Quantum probability theory is an algebraic generalization of classical (Kolmogorovian) probability theory, where an element of a (not necessarily commutative) ∗-algebra is treated as a random variable. In this aspect the concepts and methods peculiar to quantum probability are applied to the spectral analysis of adjacency matrices of graphs. In particular, we focus on the method of quantum decomposition and the use of various concepts of independence. The former discloses the noncommutative nature of adjacency matrices and gives a systematic method of computing spectral distributions. The latter is related to various graph products and provides a unified aspect in obtaining the limit spectral distributions as corollaries of various central limit theorems.

  • Primer on quantum cognition

  • Jerome R. Busemeyer, Zheng Wang
  • Journal:
    The Spanish Journal of Psychology / Volume 22 / 2019
    Published online by Cambridge University Press:
    23 December 2019, E53

  • Quantum cognition is a new field in psychology, which is characterized by the application of quantum probability theory to human judgment and decision making behavior. This article provides an introduction that presents several examples to illustrate in a simple and concrete manner how to apply these principles to interesting psychological phenomena. Following each simple example, we present the general mathematical derivations and new predictions related to these applications.