Uncertainty is an intrinsic part of life; most events, affairs, and questions are uncertain. A key
problem in behavioral sciences is how the mind copes with uncertain information. Quantum …

Classical (Bayesian) probability (CP) theory has led to an influential research tradition for
modeling cognitive processes. Cognitive scientists have been trained to work with CP …

Much of our understanding of human thinking is based on probabilistic models. This
innovative book by Jerome R. Busemeyer and Peter D. Bruza argues that, actually, the …

Written by world experts in the foundations of quantum mechanics and its applications to
social science, this book shows how elementary quantum mechanical principles can be …

The aim of this book is to demonstrate that quantum-like (QL) models, ie, models based on
the mathematical formalism of quantum mechanics (QM) and its generalizations, can be …

Two experimental tasks in psychology, the two-stage gambling game and the Prisoner's
Dilemma game, show that people violate the sure thing principle of decision theory. These …

The broader scope of our investigations is the search for the way in which concepts and their
combinations carry and influence meaning and what this implies for human thought. More …

Quantum cognition research applies abstract, mathematical principles of quantum theory to
inquiries in cognitive science. It differs fundamentally from alternative speculations about …

For decades, the dominant paradigm for studying decision making—the expected utility
framework—has been burdened by an increasing number of empirical findings that question …

Abstract The Bayesian Network is a kind of probabilistic graphical models, having been
applied to various fields for inference and learning. A quantum-like Bayesian Network has …