Articles producció científica> Enginyeria Química

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

  • Datos identificativos

    Identificador: imarina:5133293
    Autores:
    Cobo-López S, Godoy-Lorite A, Duch J, Sales-Pardo M, Guimerà R
    Resumen:
    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.
  • Otros:

    Autor según el artículo: Cobo-López S, Godoy-Lorite A, Duch J, Sales-Pardo M, Guimerà R
    Departamento: Enginyeria Informàtica i Matemàtiques Enginyeria Química
    Autor/es de la URV: Duch Gavaldà, Jordi / Guimera Manrique, Roger / Sales Pardo, Marta
    Palabras clave: Systems Stochastic block model Statistical inference Stag hunt game Social dilemmas Snowdrift game Prisoner’s dilemma Prisoner's dilemma Mixed-strategy equilibria Mixed-membership stochastic block model Harmony game Behavioural phenotypes
    Resumen: 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.
    Áreas temáticas: Social sciences, mathematical methods Modeling and simulation Mathematics, interdisciplinary applications Engenharias iv Engenharias i Computer science applications Computational mathematics Ciencias sociales Ciência da computação
    Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
    ISSN: 21931127
    Direcció de correo del autor: roger.guimera@urv.cat jordi.duch@urv.cat marta.sales@urv.cat
    Identificador del autor: 0000-0002-3597-4310 0000-0003-2639-6333 0000-0002-8140-6525
    Fecha de alta del registro: 2024-09-07
    Volumen de revista: 7
    Versión del articulo depositado: info:eu-repo/semantics/publishedVersion
    Enlace a la fuente original: https://epjdatascience.springeropen.com/articles/10.1140/epjds/s13688-018-0175-3
    URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
    Referencia al articulo segun fuente origial: Epj Data Science. 7 (1):
    Referencia de l'ítem segons les normes APA: Cobo-López S, Godoy-Lorite A, Duch J, Sales-Pardo M, Guimerà R (2018). Optimal prediction of decisions and model selection in social dilemmas using block models. Epj Data Science, 7(1), -. DOI: 10.1140/epjds/s13688-018-0175-3
    DOI del artículo: 10.1140/epjds/s13688-018-0175-3
    Entidad: Universitat Rovira i Virgili
    Año de publicación de la revista: 2018
    Página inicial: Article number 48
    Tipo de publicación: Journal Publications
  • Palabras clave:

    Computational Mathematics,Computer Science Applications,Mathematics, Interdisciplinary Applications,Modeling and Simulation,Social Sciences, Mathematical Methods
    Systems
    Stochastic block model
    Statistical inference
    Stag hunt game
    Social dilemmas
    Snowdrift game
    Prisoner’s dilemma
    Prisoner's dilemma
    Mixed-strategy equilibria
    Mixed-membership stochastic block model
    Harmony game
    Behavioural phenotypes
    Social sciences, mathematical methods
    Modeling and simulation
    Mathematics, interdisciplinary applications
    Engenharias iv
    Engenharias i
    Computer science applications
    Computational mathematics
    Ciencias sociales
    Ciência da computação
  • Documentos:

  • Cerca a google

    Search to google scholar