Humans best judge how much to cooperate when facing hard problems in large groups.

Abstract:

:We report the results of a game-theoretic experiment with human players who solve problems of increasing complexity by cooperating in groups of increasing 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 contrast, when confronting hard problems or collaborating in large groups, humans accurately judge the best level of collaboration and easily achieve the maximal 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 complexity of the situation.

journal_name

Sci Rep

journal_title

Scientific reports

authors

Guazzini A,Stefanelli F,Imbimbo E,Vilone D,Bagnoli F,Levnajić Z

doi

10.1038/s41598-019-41773-2

subject

Has Abstract

pub_date

2019-04-02 00:00:00

pages

5497

issue

1

issn

2045-2322

pii

10.1038/s41598-019-41773-2

journal_volume

9

pub_type

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