{
  "abstract": "Various theoretical and empirical studies have accounted for why humans cooperate in competitive environments. Although prior work has revealed that network structure and multiplex interactions can promote cooperation, most theory assumes that individuals play dilemma games in all social contexts. However, real-world agents may participate in a diversity of interactions, not all of which present dilemmas. We develop an evolutionary game model on multilayer networks in which one layer supports the prisoner’s dilemma game, while the other follows constant-selection dynamics, representing biased but non-dilemmatic competition, akin to opinion or fad spreading. Our theoretical analysis reveals that coupling a social dilemma layer to a non-dilemmatic constant-selection layer robustly enhances cooperation in many cases, across different multilayer networks, updating rules, and payoff schemes. These findings suggest that embedding individuals within diverse networked settings—even those unrelated to direct social dilemmas—can be a principled approach to engineering cooperation in socio-ecological and organizational systems. Author summary: Why do people cooperate even when selfish behavior looks rewarding? Network models show that who interacts with whom matters, but most assume the same kind of dilemma in every social setting. We develop a theory for populations embedded in two overlapping interaction networks: one in which individuals face a prisoner’s dilemma game, and another in which two opinions spread under competition with a built-in bias but no dilemma. We show that linking these layers can systematically increase the chance that cooperation takes over, across network structures, update rules, and how public goods are distributed. The work suggests new, principled ways to foster cooperation in dilemmatic situations by shaping non-dilemmatic social contexts.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Mathematics, State University of New York at Buffalo, Buffalo, New York, United States of America",
    "Gilbert S. Omenn Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, United States of America"
  ],
  "article_type": "Research Article",
  "arxiv": null,
  "author_total": 2,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Jnanajyoti Bhaumik"
    },
    {
      "affs": [
        1
      ],
      "name": "Naoki Masuda"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/6j6n9mw12cnbg.bib",
  "cited_by": 0,
  "doi": "10.1371/journal.pcbi.1014810",
  "fulltext_url": "https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1014810",
  "id": "6j6n9mw12cnbg",
  "issns": [
    "1553-7358"
  ],
  "landing_url": "https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1014810",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "3312|Evolutionary Game Theory and Cooperation"
    ],
    [
      "plos",
      "/Biology and life sciences/Neuroscience/Cognitive science/Cognitive psychology/Social cognition/Prosocial behavior"
    ],
    [
      "plos",
      "/Biology and life sciences/Psychology/Behavior/Prosocial behavior"
    ],
    [
      "plos",
      "/Biology and life sciences/Psychology/Cognitive psychology/Social cognition/Prosocial behavior"
    ],
    [
      "plos",
      "/Biology and life sciences/Psychology/Social psychology"
    ],
    [
      "plos",
      "/Biology and life sciences/Psychology/Social psychology/Social cognition/Prosocial behavior"
    ],
    [
      "plos",
      "/Computer and information sciences/Data management/Data visualization/Infographics/Graphs"
    ],
    [
      "plos",
      "/Computer and information sciences/Data management/Data visualization/Infographics/Graphs/Random graphs"
    ],
    [
      "plos",
      "/Computer and information sciences/Network analysis"
    ],
    [
      "plos",
      "/Physical sciences/Mathematics/Applied mathematics/Game theory"
    ],
    [
      "plos",
      "/Physical sciences/Mathematics/Applied mathematics/Game theory/Prisoner's dilemma"
    ],
    [
      "plos",
      "/Research and analysis methods/Mathematical and statistical techniques/Mathematical models/Random walk"
    ],
    [
      "plos",
      "/Social sciences/Psychology/Behavior/Prosocial behavior"
    ],
    [
      "plos",
      "/Social sciences/Psychology/Cognitive psychology/Social cognition/Prosocial behavior"
    ],
    [
      "plos",
      "/Social sciences/Psychology/Social psychology"
    ],
    [
      "plos",
      "/Social sciences/Psychology/Social psychology/Social cognition/Prosocial behavior"
    ]
  ],
  "openalex": "W7118261023",
  "pdf_url": "https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1014810&type=printable",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-23",
  "publisher": "Public Library of Science",
  "ris": "https://research.draconitic.com/paper/6j6n9mw12cnbg.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:43Z",
      "native_id": "10.1371/journal.pcbi.1014810",
      "source": "plos",
      "url": "https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1014810"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "plos:neuroscience",
      "subfield": "neuroscience"
    }
  ],
  "title": "Coupling with opinion dynamics promotes prosocial behavior in multilayer networks",
  "title_text": "Coupling with opinion dynamics promotes prosocial behavior in multilayer networks",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:17:43Z",
  "url": "https://research.draconitic.com/paper/6j6n9mw12cnbg",
  "venue": "PLOS Computational Biology",
  "versions": []
}