Literature DB >> 29606900

Leveraging Statistical Physics to Improve Understanding of Cooperation in Multiplex Networks.

Feng Fu1,2, Xingru Chen1.   

Abstract

Understanding how public cooperation emerges and is maintained is a topic of broad interest, with increasing contributions coming from a synergistic combination of evolutionary game theory and statistical physics. The comprehensive study by Battiston et al (2017 New J. Phys., in press) improves our understanding of the role of multiplexity in cooperation, revealing that a significant edge overlap across network layers along with benign conditions for cooperation in at least one of the layers is needed to facilitate the emergence of cooperation in the multiplex.

Entities:  

Year:  2017        PMID: 29606900      PMCID: PMC5875177          DOI: 10.1088/1367-2630/aa78c1

Source DB:  PubMed          Journal:  New J Phys        ISSN: 1367-2630            Impact factor:   3.729


  4 in total

Review 1.  Five rules for the evolution of cooperation.

Authors:  Martin A Nowak
Journal:  Science       Date:  2006-12-08       Impact factor: 47.728

2.  Evolutionary dynamics in set structured populations.

Authors:  Corina E Tarnita; Tibor Antal; Hisashi Ohtsuki; Martin A Nowak
Journal:  Proc Natl Acad Sci U S A       Date:  2009-05-11       Impact factor: 11.205

3.  Intuition, deliberation, and the evolution of cooperation.

Authors:  Adam Bear; David G Rand
Journal:  Proc Natl Acad Sci U S A       Date:  2016-01-11       Impact factor: 12.779

4.  The evolution of homophily.

Authors:  Feng Fu; Martin A Nowak; Nicholas A Christakis; James H Fowler
Journal:  Sci Rep       Date:  2012-11-13       Impact factor: 4.379

  4 in total
  2 in total

1.  Evolutionary dynamics of higher-order interactions in social networks.

Authors:  Unai Alvarez-Rodriguez; Federico Battiston; Guilherme Ferraz de Arruda; Yamir Moreno; Matjaž Perc; Vito Latora
Journal:  Nat Hum Behav       Date:  2021-01-04

2.  Seasonal payoff variations and the evolution of cooperation in social dilemmas.

Authors:  Attila Szolnoki; Matjaž Perc
Journal:  Sci Rep       Date:  2019-08-29       Impact factor: 4.379

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.