Jove
Visualize
Contact Us

Related Concept Videos

Confirmation Biases01:31

Confirmation Biases

5.6K
The confirmation bias is the tendency to focus on information that confirms our existing beliefs and ignore information that is inconsistent with our expectations. For example, if you think that your professor is not very nice, you notice all of the instances of rude behavior exhibited by the professor while ignoring the countless pleasant interactions he is involved in on a daily basis. Have you ever fallen prey to the confirmation bias, either as the source or target of such bias?
5.6K
Stereotype Content Model02:16

Stereotype Content Model

14.8K
The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
14.8K
Hindsight Biases01:12

Hindsight Biases

3.5K
Hindsight bias leads you to believe that the event you just experienced was predictable, even though it really wasn’t. In other words, you knew all along that things would turn out the way they did. Can you relate this to the phrase "Hindsight is 20/20" now? 
3.5K
Evolutionary Psychology01:20

Evolutionary Psychology

365
Evolutionary psychology explores the origins of human behavior and mental processes by framing them within the context of natural selection, a theory famously propounded by Charles Darwin. This field asserts that many behaviors common across human societies — ranging from instinctive fear reactions to complex social interactions — arose as evolutionary adaptations. These adaptations enhanced the survival and reproductive success of our ancestors, thereby becoming embedded in the...
365
Types of Selection01:46

Types of Selection

41.1K
Natural selection influences the frequencies of particular alleles and phenotypes within populations in several different ways. Primarily, natural selection can be directional, stabilizing, or disruptive. Directional selection favors one extreme trait and shifts the population towards that phenotype while selecting against individuals displaying alternate traits. Stabilizing selection favors an intermediate trait with a narrow range of variation. Deviation from the optimal phenotype towards an...
41.1K
Bias01:22

Bias

4.7K
Bias refers to any tendency that prevents a question from being considered unprejudiced. In research, bias occurs when one outcome or answer is selected or encouraged over others in sampling or testing. Bias can occur during any research phase, including study design, data collection, analysis, and publication.
In statistics, a sampling bias is created when a sample is collected from a population, and some members of the population are not as likely to be chosen as others (remember, each member...
4.7K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Kink scattering in deformed φ^{6} model.

Physical review. E·2025
Same author

A Quantum-Like Model for Predicting Human Decisions in the Entangled Social Systems.

IEEE transactions on cybernetics·2022
Same author

Soliton-potential interaction in the phi(4) model.

Physical review. E, Statistical, nonlinear, and soft matter physics·2009
Same author

Analytical formulation for soliton-potential dynamics.

Physical review. E, Statistical, nonlinear, and soft matter physics·2008
Same author

V-Lab-a virtual laboratory for autonomous agents-SLA-based learning controllers.

IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society·2008
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Video

Updated: Aug 15, 2025

Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues
07:34

Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues

Published on: June 3, 2013

17.4K

A quantum-like cognitive approach to modeling human biased selection behavior.

Aghdas Meghdadi1, M R Akbarzadeh-T2, Kurosh Javidan3

  • 1Department of Electrical Engineering, Center of Excellence on Soft Computing and Intelligent Information Processing, Ferdowsi University of Mashhad, Mashhad, Iran.

Scientific Reports
|December 29, 2022
PubMed
Summary

This study introduces a novel quantum-like Bayesian network (QBN) to model cognitive biases in human decision-making. The biased entangled QBN (BEQBN) model shows superior predictive accuracy for human behaviors compared to classical and other QBN approaches.

More Related Videos

Assessment of Mouse Judgment Bias through an Olfactory Digging Task
12:10

Assessment of Mouse Judgment Bias through an Olfactory Digging Task

Published on: March 4, 2022

2.7K
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

7.6K

Related Experiment Videos

Last Updated: Aug 15, 2025

Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues
07:34

Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues

Published on: June 3, 2013

17.4K
Assessment of Mouse Judgment Bias through an Olfactory Digging Task
12:10

Assessment of Mouse Judgment Bias through an Olfactory Digging Task

Published on: March 4, 2022

2.7K
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

7.6K

Area of Science:

  • Cognitive Science
  • Quantum Physics
  • Computational Social Science

Background:

  • Human decision-making is significantly influenced by cognitive biases, which are often overlooked in behavioral modeling.
  • Classical models struggle to capture the irrational aspects of human choices driven by biases.
  • Existing quantum-like approaches do not fully account for social influences on individual biases.

Purpose of the Study:

  • To develop a novel cognitive quantum-like approach for modeling human biases in decision-making.
  • To introduce a biased entangled Quantum-like Bayesian Network (BEQBN) model incorporating social entanglement.
  • To enhance the prediction of human selection behaviors by accounting for cognitive biases.

Main Methods:

  • Simulated society as a quantum system using a Quantum-like Bayesian Network (QBN) structure.
  • Developed an improved entangled QBN approach inspired by electric fields to model initial biases.
  • Introduced a bias potential function and a quantum-like entanglement witness in Hilbert space for the BEQBN model.

Main Results:

  • The proposed biased entangled QBN (BEQBN) model effectively incorporates social entanglement and bias potential.
  • BEQBN achieved the first rank in predictive accuracy on two empirical tasks.
  • The model demonstrated superior performance compared to classical Bayesian Networks and six other QBN approaches.

Conclusions:

  • The BEQBN model provides a more realistic prediction of human behaviors by integrating cognitive biases.
  • Quantum-like modeling, particularly with social entanglement, offers a powerful framework for understanding decision-making.
  • This approach highlights the importance of considering agents as part of a social system rather than isolated entities.