Next Article in Journal
A New Image Encryption Algorithm Based on Composite Chaos and Hyperchaos Combined with DNA Coding
Next Article in Special Issue
On the Irrationality of Being in Two Minds
Previous Article in Journal
Application of Time-Scale Decomposition of Entropy for Eye Movement Analysis
Previous Article in Special Issue
Adapting Logic to Physics: The Quantum-Like Eigenlogic Program
Open AccessArticle

Balanced Quantum-Like Bayesian Networks

1
Department of Computer Science and Engineering, INESC-ID & Instituto Superior Técnico, University of Lisbon, 2740-122 Porto Salvo, Portugal
2
School of Information Systems, Science and Engineering Faculty, Queensland University of Technology, QLD 4000 Brisbane, Australia
*
Author to whom correspondence should be addressed.
Entropy 2020, 22(2), 170; https://doi.org/10.3390/e22020170
Received: 15 December 2019 / Revised: 29 January 2020 / Accepted: 30 January 2020 / Published: 2 February 2020
(This article belongs to the Special Issue Quantum Information Revolution: Impact to Foundations)
Empirical findings from cognitive psychology indicate that, in scenarios under high levels of uncertainty, many people tend to make irrational decisions. To address this problem, models based on quantum probability theory, such as the quantum-like Bayesian networks, have been proposed. However, this model makes use of a Bayes normalisation factor during probabilistic inference to convert the likelihoods that result from quantum interference effects into probability values. The interpretation of this operation is not clear and leads to extremely skewed intensity waves that make the task of prediction of these irrational decisions challenging. This article proposes the law of balance, a novel mathematical formalism for probabilistic inferences in quantum-like Bayesian networks, based on the notion of balanced intensity waves. The general idea is to balance the intensity waves resulting from quantum interference in such a way that, during Bayes normalisation, they cancel each other. With this representation, we also propose the law of maximum uncertainty, which is a method to predict these paradoxes by selecting the amplitudes of the wave with the highest entropy. Empirical results show that the law of balance together with the law of maximum uncertainty were able to accurately predict different experiments from cognitive psychology showing paradoxical or irrational decisions, namely in the Prisoner’s Dilemma game and the Two-Stage Gambling Game.
Keywords: decision making; quantum cognition; quantum-like Bayesian networks; law of total probability; probability waves decision making; quantum cognition; quantum-like Bayesian networks; law of total probability; probability waves
MDPI and ACS Style

Wichert, A.; Moreira, C.; Bruza, P. Balanced Quantum-Like Bayesian Networks. Entropy 2020, 22, 170.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop