©Copyright JASSS

JASSS logo ----

Rainer Hegselmann and Ulrich Krause (2006)

Truth and Cognitive Division of Labour: First Steps Towards a Computer Aided Social Epistemology

Journal of Artificial Societies and Social Simulation vol. 9, no. 3

For information about citing this article, click here

Received: 29-Jul-2005    Accepted: 21-May-2006    Published: 30-Jun-2006

PDF version

* 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.

Opinion Dynamics, Consensus/dissent, Bounded Confidence, Truth, Social Epistemology

Because of the complex mathematical notation in this article, it is only available in Portable Document Format (PDF) format.

The article is here.

* References

ABELSON, R P (1964), "Mathematical models of the distribution of attitudes under controversy". In Frederiksen N and Gulliksen H (Eds.), Contributions to Mathematical Psychology, New York, NY: Holt, Rinehart, and Winston.

BECKMANN T (1997) Starke und schwache Ergodizität in nichtlinearen Konsensmodellen. Diploma thesis: Universität Bremen, 64 p.

BOGDAN R J (Ed) (1981) Keith Lehrer, Dordrecht: D. Reidel Publ. Co.

CHATTERJEE S (1975) Reaching a consensus: Some limit theorems. Proc. Int. Statist. Inst. pp. 159–164.

CHATTERJEE S and Seneta E (1977) Toward consensus: some convergence theorems on repeated averaging. J. Appl. Prob. 14. pp. 89–97.

CHESNEVAR I C, Maguitman A G and Loui R P (2000) Logical Models of Argument. ACM Computing Surveys (CSUR) Volume 32, Issue 4 (December 2000) Pages: 337–383.

DEFFUANT G, Neau D, Amblard F and Weisbuch G (2000) Mixing beliefs among interact- ing agents. Advances in Complex Systems 3. pp. 87–98.

DE GROOT M H (1974) Reaching a consensus. J. Amer. Statist. Assoc. 69. pp. 118–121.

DITTMER J C (2000) Diskrete nichtlineare Modelle der Konsensbildung. Diploma thesis: Universität Bremen.

DITTMER J C (2001) Consensus formation under bounded confidence. Nonlinear Analysis 7. pp. 4615–4621.

ENGEL, P (2004) "Truth and the Aim of Belief". In Gillies D. (Ed), Laws and Models in Science. London: King's College Publications. pp. 79–99.

FORTUNATO S (2004) The Krause–Hegselmann consensus model with discrete opinions, Int. J. Mod. Phys. C15 (7).

FORTUNATO S (2005) On the Consensus Threshold for the Opinion Dynamics of Krause – Hegselmann. Cond-mat/0408648 at www.arXiv.org. To appear in Int. J. Mod. Phys. C16, issue 2.

FORTUNATO S, Latora V, Pluchino A and Rapisarda A (2005) Vector Opionion Dynamics in a Bounded Confidence Consensus Model. International Journal of Modern Physics C (to appear).

FORTUNATO S and Stauffer D (2005) "Computer Simulations of Opinions and Their Reac- tions to Extreme Events". In Albeverio S, Jentsch V and Kantz H (Eds), Extreme Events in Nature and Society, Heidelberg: Springer. To appear.

FRENCH J R P (1956) A formal theory of social power. Psychological Review 63. pp. 181– 194.

FRIEDKIN N E and Johnsen E C (1990) Social influence and opinions, J. Math. Soc. 15. pp. 193–206.

FULLER S (2002) Social Epistemology. Bloomington, Indiana UP, 1st ed. 1988.

GALAM S, Gefen Y and Shapin Y (1982) Sociophysics: A mean behavior model for the process of strike. J. Math. Soc. 9, 1–13.

GALAM S and Moscovici S (1991) Towards a Theory of Collective Phenomena: Consensus and Attitude Changes in Groups. European Journal of Social Psychology 21, pp. 49–74.

GOLDMAN A (1999) Knowledge in a Social World. Oxford: Oxford University Press.

GOLDMAN A (2001) "Social epistemology". In Stanford Encyclopedia of Philosophy. http://plato.stanford.edu/entries/epistemology-social/

HABERMAS J (1973) "Wahrheitstheorien". In Fahrenbach H (Ed), Wirklichkeit und Reflexion – Walter Schulz zum 60. Geburtstag, Pfullingen: Neske. pp. 211–265.

HARARY F (1959) "A criterion for unanimity in French’s theory of social power". In Cartwright D (Ed.), Studies in Social Power. Ann Arbor: Institute for Social Research.

HEGSELMANN R, Flache A and Möller V (1999), "Cellular Automata Models of Solidarity and Opinion Formation: Sensitivity Analysis". In Suleiman R, Troitzsch K G and Gilbert N 27 (Eds), Social Science Microsimulation – Tools for Modeling – Parameter Optimization and Sensitivity Analysis, Heidelberg: Physica–Verlag. pp. 151–178.

HEGSELMANN R and Krause U (2002) Opinion Dynamics and Bounded Confidence – Models, Analysis, and Simulations. Journal of Artificial Societies and Social Simulation (JASSS) vol.5, no. 3 https://www.jasss.org/5/3/2.html.

HEGSELMANN R and Krause U (2005) Opinion Dynamics Driven by Various Ways of Averaging. Computational Economics 25. pp. 381–405.

HEGSELMANN R (2004) "Opinion Dynamics – Insights by Radically Simplifying Models" In Gillies D (Ed), Laws and Models in Science, London: King's College Publications. pp. 19– 46.

HEGSELMANN R (2004a), Das Trichter-Theorem. Bayreuth: Manuscript.

KRAUSE U (1997), "Soziale Dynamiken mit vielen Interakteuren. Eine Problemskizze". In Krause U and Stöckler M (Eds.), Modellierung und Simulation von Dynamiken mit vielen interagierenden Akteuren, Universität Bremen. pp. 37 – 51.

KRAUSE U (2000), "A discrete nonlinear and non—autonomous model of consensus forma- tion". In Elaydi S, Ladas G, Popenda J and Rakowski J (Eds.), Communications in Difference Equations, Amsterdam: Gordon and Breach Publ.. pp. 227 – 236.

KRAUSE U (2003), "Positive particle interaction". In Benvenuti L, De Santis A and Farina L (Eds.), Positive Systems, Berlin etc.: Springer. pp. 199–206.

KRAUSE U (2005), "Time variant consensus formation in higher dimensions". In Elaydi S, Ladas G, Aulbach B and Dosley O (Eds), Proceedings of the 8th International Conference on Difference Equations and Applications, 2003, Boca Raton etc.: Chapman & Hall/CRC. pp. 185–191.

KRAUSE U and Nesemann T (1999) Differenzengleichungen und diskrete dynamische Systeme, Leipzig: Teubner.

KUIPERS, T A F (2000) From Instrumentalism to Constructive Realism. On Some Relations between Confirmation, Empirical Progress, and Truth Approximation. Synthese Library, Volume 287. Dordrecht: Kluwer Academic Publishers.

LEHRER K (1975) Social Consensus and Rational Agnoiology. Synthese 31. pp. 141–160.

LEHRER K (1976) When rational disagreement is impossible. Nous 10. pp. 327–332.

LEHRER K (1977) Social Information. The Monist 60. pp. 473–487.

LEHRER K (1981), "A Self Profile". In Bogdan R J (Ed), Keith Lehrer, Dordrecht: D. Reidel Publ. Co.. pp. 3–104.

LEHRER K (1981a)," Replies". In Bogdan R J (Ed), Keith Lehrer, Dordrecht 1981: D. Reidel Publ. Co.. pp. 223–242.

LEHRER K (1985) Consensus and the Ideal Observer. Synthese 62. pp. 109–120.

LEHRER K and Wagner C G (1981) Rational Consensus in Science and Society. Dordrecht: D. Reidel Publ. Co.

LEVI I (1985) Consensus as Shared Agreement and Outcome of Inquiry. Synthese 62. pp. 3– 11.

LOEWER B (Ed) (1985) Consensus. Synthese 62 (special issue). 28

LORENZ J (2003) Mehrdimensionale Meinungsdynamik bei wechselndem Vertrauen. Diploma Thesis: Universität Bremen. http://wwwstuga.informatik.uni-bremen.de/mathematik/-archiv/diplome/jlorenz.zip.

LORENZ J (2003a) Opinion dynamics with different confidence bounds for the agents. Preprint, www.janlo.de.

LORENZ J (2005) A stabilization theorem for dynamics of continuous opinions. Physica A, 355(1). pp. 217–223.

NOWAK A, Szamrez J and Latane B (1990) From private attitude to public opinion – Dynamic theory of social impact. Psych. Review 97. pp. 362-376.

SCHMITT F (1999), "Social Epistemology". In Greco J, Sosa E (Eds.), The Blackwell Guide to Epistemology. Oxford: Blackwell. pp. 354-382.

SCHMITT F (1994), Socializing Epistemology – The Social Dimensions of Knowledge. Lanham: Rowman & Littlelfield Publishers, Inc.

SZNAJD–WERON K and Sznajd J (2000) Opinion evolution in closed community. International Journal of Modern Physics C 11. pp. 1157-1166.

STAUFFER D (2002) Monte Carlo simulations of the Sznajd model. Journal of Artificial Societies and Social Simulations, vol. 5, no. 1. https://www.jasss.org/5/1/4.html.

STAUFFER D (2003) How to convince others? American Institute of Physics, Conference Proceedings 690, pp. 147-155.

STAUFFER D (2004) Difficulty for consensus in simultaneous opinion formation of Sznajd model. J. Math. Soc. 28. pp. 25-33.

URBIG D and Lorenz J (2004) Communication regimes in opinion dynamics: Changing the number of communicating agents. Proceedings of the Second Conference of the European Social Simulation Association (ESSA).

WEISBUCH G, Deffuant G, Amblard F and Nadal J P (2001) Interacting agents and continuous opinion dynamics. http://arXiv.org/pdf/cond-mat/0111494.


ButtonReturn to Contents of this issue

© Copyright Journal of Artificial Societies and Social Simulation, [2006]