Citing this article

A standard form of citation of this article is:

Hegselmann, Rainer and Krause, Ulrich (2006). 'Truth and Cognitive Division of Labour: First Steps Towards a Computer Aided Social Epistemology'. Journal of Artificial Societies and Social Simulation 9(3)10 <https://www.jasss.org/9/3/10.html>.

The following can be copied and pasted into a Bibtex bibliography file, for use with the LaTeX text processor:

@article{hegselmann2006,
title = {Truth and Cognitive Division of Labour: First Steps Towards a Computer Aided Social Epistemology},
author = {Hegselmann, Rainer and Krause, Ulrich},
journal = {Journal of Artificial Societies and Social Simulation},
ISSN = {1460-7425},
volume = {9},
number = {3},
pages = {10},
year = {2006},
URL = {https://www.jasss.org/9/3/10.html},
keywords = {Opinion Dynamics, Consensus/dissent, Bounded Confidence, Truth, Social Epistemology},
abstract = {The paper analyzes the chances for the truth to be found and broadly accepted under conditions of cognitive division of labour combined with a social exchange process. Cognitive division of labour means, that only some individuals are active truth seekers, possibly with different capacities. The social exchange process consists in an exchange of opinions between all individuals, whether truth seekers or not. We de- velop a model which is investigated by both, mathematical tools and computer simulations. As an analytical result the Funnel theorem states that under rather weak conditions on the social process a consensus on the truth will be reached if all individuals posses an arbitrarily small inclination for truth seeking. The Leading the pack theorem states that under certain conditions even a single truth seeker may lead all individuals to the truth. Systematic simulations analyze how close and how fast groups can get to the truth depending on the frequency of truth seekers, their capacities as truth seekers, the position of the truth (more to the extreme or more in the centre of an opinion space), and the willingness to take into account the opinions of others when exchanging and updating opinions. A tricky movie visualizes simulations results in a parameter space of higher dimensions.},
}

The following can be copied and pasted into a text file, which can then be imported into a reference database that supports imports using the RIS format, such as Reference Manager and EndNote.


TY - JOUR
TI - Truth and Cognitive Division of Labour: First Steps Towards a Computer Aided Social Epistemology
AU - Hegselmann, Rainer
AU - Krause, Ulrich
Y1 - 2006/06/30
JO - Journal of Artificial Societies and Social Simulation
SN - 1460-7425
VL - 9
IS - 3
SP - 10
UR - https://www.jasss.org/9/3/10.html
KW - Opinion Dynamics
KW - Consensus/dissent
KW - Bounded Confidence
KW - Truth
KW - Social Epistemology
N2 - The paper analyzes the chances for the truth to be found and broadly accepted under conditions of cognitive division of labour combined with a social exchange process. Cognitive division of labour means, that only some individuals are active truth seekers, possibly with different capacities. The social exchange process consists in an exchange of opinions between all individuals, whether truth seekers or not. We de- velop a model which is investigated by both, mathematical tools and computer simulations. As an analytical result the Funnel theorem states that under rather weak conditions on the social process a consensus on the truth will be reached if all individuals posses an arbitrarily small inclination for truth seeking. The Leading the pack theorem states that under certain conditions even a single truth seeker may lead all individuals to the truth. Systematic simulations analyze how close and how fast groups can get to the truth depending on the frequency of truth seekers, their capacities as truth seekers, the position of the truth (more to the extreme or more in the centre of an opinion space), and the willingness to take into account the opinions of others when exchanging and updating opinions. A tricky movie visualizes simulations results in a parameter space of higher dimensions.
ER -