Quantum machine learning is a rapidly growing field at the intersection of quantum
technology and artificial intelligence. This review provides a two-fold overview of several key …

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 …

Quantum Machine Learning bridges the gap between abstract developments in quantum
computing and the applied research on machine learning. Paring down the complexity of the …

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 …

What type of probability theory best describes the way humans make judgments under
uncertainty and decisions under conflict? Although rational models of cognition have …

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 …

A quantum probability model is introduced and used to explain human probability judgment
errors including the conjunction and disjunction fallacies, averaging effects, unpacking …

The hypothesis that human reasoning obeys the laws of quantum rather than classical
probability has been used in recent years to explain a variety of seemingly “irrational” …

Question order effects are commonly observed in self‐report measures of judgment and
attitude. This article develops a quantum question order model (the QQ model) to account for …