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Optimal prediction of decisions and model selection in social dilemmas using block models.

Authors :
Cobo-López, Sergio
Godoy-Lorite, Antonia
Duch, Jordi
Sales-Pardo, Marta
Guimerà, Roger
Source :
EPJ Data Science; 11/14/2018, Vol. 7 Issue 1, p1-1, 1p
Publication Year :
2018

Abstract

Advancing our understanding of human behavior hinges on the ability of theories to unveil the mechanisms underlying such behaviors. Measuring the ability of theories and models to predict unobserved behaviors provides a principled method to evaluate their merit and, thus, to help establish which mechanisms are most plausible. Here, we propose models and develop rigorous inference approaches to predict strategic decisions in dyadic social dilemmas. In particular, we use bipartite stochastic block models that incorporate information about the dilemmas faced by individuals. We show, combining these models with empirical data on strategic decisions in dyadic social dilemmas, that individual strategic decisions are to a large extent predictable, despite not being “rational.” The analysis of these models also allows us to conclude that: (i) individuals do not perceive games according their game-theoretical structure; (ii) individuals make decisions using combinations of multiple simple strategies, which our approach reveals naturally. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
21931127
Volume :
7
Issue :
1
Database :
Complementary Index
Journal :
EPJ Data Science
Publication Type :
Academic Journal
Accession number :
133019828
Full Text :
https://doi.org/10.1140/epjds/s13688-018-0175-3