Humans Make Best Use of Social Heuristics When Confronting Hard Problems in Large Groups
Humans make best use of social heuristics when confronting hard problems in large groups Federica Stefanelli1, Enrico Imbimbo1, Daniele Vilone2,3, Franco Bagnoli4, Zoran Levnaji´c5, Andrea Guazzini1 1Department of Education and Psychology, University of Florence, Florence, Italy 2Laboratory of Agent Based Social Simulation, Institute of Cognitive Science and Technology, National Research Council (CNR), Rome, Italy; 3Grupo Interdisciplinar de Sistemas Complejos (GISC), Departamento de Matem´aticas, Universidad Carlos III de Madrid, Spain 4Department of Physics and Astronomy & Center for Study of Complex Dynamics, University of Florence and INFN, Florence, Italy 5Faculty of Information Studies in Novo mesto, Novo Mesto, Slovenia Abstract We report the results of a game-theoretic experiment with human players who solve the problems of increasing complexity by cooperating in groups of increas- ing size. Our experimental environment is set up to make it complicated for players to use rational calculation for making the cooperative decisions. This environment is directly translated into a computer simulation, from which we extract the collaboration strategy that leads to the maximal attainable score. Based on this, we measure the error that players make when estimating the benefits of collaboration, and find that humans massively underestimate these benefits when facing easy problems or working alone or in small groups. In con- trast, when confronting hard problems or collaborating in large groups, humans accurately judge the best level of collaboration and easily achieve the maxi- mal score. Our findings are independent on groups’ composition and players’ personal traits. We interpret them as varying degrees of usefulness of social heuristics, which seems to depend on the size of the involved group and the arXiv:1808.07670v2 [physics.soc-ph] 8 Mar 2019 complexity of the situation.
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