Individual decision making in task-oriented groups

  • Sandro M. Reia
  • Paulo F. Gomes
  • José F. FontanariEmail author
Regular Article


The strategies adopted by individuals to select relevant information to pass on are central to understanding problem solving by groups. Here we use agent-based simulations to revisit a cooperative problem-solving scenario where the task is to find the common card in decks distributed to the group members. The agents can display only a sample of their cards and we explore different strategies to select those samples based on the confidences assigned to the cards. An agent’s confidence that a particular card is the correct one is given by the number of times it observed that card in the decks of the other agents. We use a Gibbs distribution to select the card samples with the temperature measuring the strength of a noise that prevents the agents to correctly rank the cards. The group is guaranteed to find the common card in all runs solely in the infinite temperature limit, where the cards are sampled regardless of their confidences. In this case, we obtain the scaling form of the time constant that characterizes the asymptotic exponential decay of the failure probability. For finite time, however, a finite temperature yields a probability of failure that is several orders of magnitude lower than in the infinite temperature limit. The available experimental results are consistent with the decision-making model for finite temperature only.

Graphical abstract


Statistical and Nonlinear Physics 


  1. 1.
    H.A. Simon, Models of Man: Social and Rational (John Wiley & Sons, New York, 1957) Google Scholar
  2. 2.
    A. Newell, Unified Theories of Cognition (Harvard University Press, Cambridge, MA, 1994) Google Scholar
  3. 3.
    H.J. Leavitt, J. Abnorm. Soc. Psych. 46, 38 (1951) Google Scholar
  4. 4.
    A. Bavelas, J. Acoustical Soc. Am. 22, 725 (1950) Google Scholar
  5. 5.
    G.A. Heise, G.A. Miller, J. Abnorm. Soc. Psych. 46, 327 (1951) Google Scholar
  6. 6.
    H. Guetzkow, H.A. Simon, Manag. Sci. 1, 233 (1955) CrossRefGoogle Scholar
  7. 7.
    M.E. Shaw, J. Abnorm. Soc. Psych. 49, 547 (1954) Google Scholar
  8. 8.
    M. Mulder, Sociometry 23, 1 (1960) CrossRefGoogle Scholar
  9. 9.
    W. Mason, D.J. Watts, Proc. Natl. Acad. Sci. 109, 764 (2012) ADSCrossRefGoogle Scholar
  10. 10.
    S.M. Reia, S. Herrmann, J.F. Fontanari, Phys. Rev. E 95, 022305 (2017) ADSCrossRefGoogle Scholar
  11. 11.
    S.H. Clearwater, B.A. Huberman, T. Hogg, Science 254, 1181 (1991) ADSCrossRefGoogle Scholar
  12. 12.
    J. Kennedy, Adapt. Behav. 7, 269 (1999) CrossRefGoogle Scholar
  13. 13.
    D. Lazer, A. Friedman, Admin. Sci. Quart. 52, 667 (2007) CrossRefGoogle Scholar
  14. 14.
    J.F. Fontanari, Eur. Phys. J. B 88, 251 (2015) ADSCrossRefGoogle Scholar
  15. 15.
    J.F. Fontanari, Cogn. Syst. Res. 50, 29 (2018) CrossRefGoogle Scholar
  16. 16.
    V. Privman, Finite-Size Scaling and Numerical Simulations of Statistical Systems (World Scientific, Singapore, 1990) Google Scholar
  17. 17.
    W. Feller, in An Introduction to Probability Theory and Its Applications, 3rd edn. (Wiley, New York, 1968), Vol. 1 Google Scholar
  18. 18.
    S.E. Page, The Difference: How the Power of Diversity Creates Better Groups, Firms, Schools, and Societies (Princeton University Press, Princeton, 2007) Google Scholar
  19. 19.
    J.M. Levine, L.B. Resnick, E.T. Higgins, Annu. Rev. Psychol. 44, 585 (1993) CrossRefGoogle Scholar
  20. 20.
    A.W. Woolley, C.F. Chabris, A. Pentland, N.H.T. Malone, Science 333, 686 (2010) ADSCrossRefGoogle Scholar
  21. 21.
    P.F.C. Tilles, J.F. Fontanari, Europhys. Lett. 99, 60001 (2012) ADSCrossRefGoogle Scholar
  22. 22.
    R. Reisenauer, K. Smith, R.A. Blythe, Phys. Rev. Lett. 110, 258701 (2013) ADSCrossRefGoogle Scholar
  23. 23.
    E.T. Jaynes, Probability Theory: The Logic of Science (Cambridge University Press, Cambridge, UK, 2003) Google Scholar
  24. 24.
    G.B. West, Scale: The Universal Laws of Growth, Innovation, Sustainability, and the Pace of Life in Organisms, Cities, Economies, and Companies (Penguim Press, New York, 2017) Google Scholar

Copyright information

© EDP Sciences / Società Italiana di Fisica / Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Instituto de Física de São Carlos, Universidade de São PauloSão PauloBrazil
  2. 2.Instituto de Ciências Exatas e Tecnológicas, Universidade Federal de GoiásGoiásBrazil

Personalised recommendations