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 …

Modeling human cognition is challenging because there are infinitely many mechanisms
that can generate any given observation. Some researchers address this by constraining 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 …

There is an underlying assumption in the social sciences that consciousness and social life
are ultimately classical physical/material phenomena. In this ground-breaking book …

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 …

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

Recently, the popularity of using the expressive power of quantum computing to solve
known, challenging problems has increased remarkably. This study aims to develop a clear …

This short review presents a selected history of the mutual fertilization between physics and
economics—from Isaac Newton and Adam Smith to the present. The fundamentally different …