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Tracking the Evolution of Cooperation in Complex Networked Populations

  • Conference paper
Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics (EvoBIO 2012)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7246))

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Abstract

Social networks affect in such a fundamental way the dynamics of the population they support that the global, population-wide behavior that one observes often bears no relation to the agent processes it stems from. Up to now, linking the global networked dynamics to such agent mechanisms has remained elusive. Here we define an observable dynamic and use it to track the self-organization of cooperators when co-evolving with defectors in networked populations interacting via a Prisoner’s Dilemma. Computations on homogeneous networks evolve towards the coexistence between cooperator and defector agents, while computations in heterogeneous networks lead to the coordination between them. We show how the global dynamics co-evolves with the motifs of cooperator agents in the population, the overall emergence of cooperation depending sensitively on this co-evolution.

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Author information

Authors and Affiliations

  1. Instituto para a Investigacao Interdisciplinar, ATP-Group, CMAF, P-1649-003, Lisboa Codex, Portugal

    Flávio L. Pinheiro, Francisco C. Santos & Jorge M. Pacheco

  2. Departamento de Engenharia Informática, Instituto Superior Técnico, Universidade Técnica de Lisboa, Av. Rovisco Pais, 1, 1049-001, Lisboa, Portugal

    Francisco C. Santos

  3. Departamento de Matemática e Aplicações, Universidade do Minho, 4710 - 057, Braga, Portugal

    Jorge M. Pacheco

Authors
  1. Flávio L. Pinheiro
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  2. Francisco C. Santos
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  3. Jorge M. Pacheco
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Editor information

Editors and Affiliations

  1. Department of Animal Production Epidemiology and Ecology, University of Torino, Via Leonardo da Vinci 44, 10095, Grugliasco, (TO), Italy

    Mario Giacobini

  2. Universidade Nove de Lisboa, ISEGI, 1070-312 Lisboa, Portugal and University of Milano-Bicocca, D.I.S.Co., Viale Sarca 336, 20126 Milan, Italy

    Leonardo Vanneschi

  3. Center for Human Genetics Research, Department of Biomedical Informatics, Vanderbilt University, 519 Light Hall, 37232, Nashville, TN, USA

    William S. Bush

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© 2012 Springer-Verlag Berlin Heidelberg

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Pinheiro, F.L., Santos, F.C., Pacheco, J.M. (2012). Tracking the Evolution of Cooperation in Complex Networked Populations. In: Giacobini, M., Vanneschi, L., Bush, W.S. (eds) Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics. EvoBIO 2012. Lecture Notes in Computer Science, vol 7246. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29066-4_8

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  • DOI: https://doi.org/10.1007/978-3-642-29066-4_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-29065-7

  • Online ISBN: 978-3-642-29066-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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