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Scaffolding cooperation in human groups with deep reinforcement learning

Author

Listed:
  • Kevin R. McKee

    (Google DeepMind)

  • Andrea Tacchetti

    (Google DeepMind)

  • Michiel A. Bakker

    (Google DeepMind)

  • Jan Balaguer

    (Google DeepMind)

  • Lucy Campbell-Gillingham

    (Google DeepMind)

  • Richard Everett

    (Google DeepMind)

  • Matthew Botvinick

    (Google DeepMind
    University College London)

Abstract

Effective approaches to encouraging group cooperation are still an open challenge. Here we apply recent advances in deep learning to structure networks of human participants playing a group cooperation game. We leverage deep reinforcement learning and simulation methods to train a ‘social planner’ capable of making recommendations to create or break connections between group members. The strategy that it develops succeeds at encouraging pro-sociality in networks of human participants (N = 208 participants in 13 groups) playing for real monetary stakes. Under the social planner, groups finished the game with an average cooperation rate of 77.7%, compared with 42.8% in static networks (N = 176 in 11 groups). In contrast to prior strategies that separate defectors from cooperators (tested here with N = 384 in 24 groups), the social planner learns to take a conciliatory approach to defectors, encouraging them to act pro-socially by moving them to small highly cooperative neighbourhoods.

Suggested Citation

  • Kevin R. McKee & Andrea Tacchetti & Michiel A. Bakker & Jan Balaguer & Lucy Campbell-Gillingham & Richard Everett & Matthew Botvinick, 2023. "Scaffolding cooperation in human groups with deep reinforcement learning," Nature Human Behaviour, Nature, vol. 7(10), pages 1787-1796, October.
  • Handle: RePEc:nat:nathum:v:7:y:2023:i:10:d:10.1038_s41562-023-01686-7
    DOI: 10.1038/s41562-023-01686-7
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    References listed on IDEAS

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    Cited by:

    1. Atsushi Ueshima & Matthew I. Jones & Nicholas A. Christakis, 2024. "Simple autonomous agents can enhance creative semantic discovery by human groups," Nature Communications, Nature, vol. 15(1), pages 1-11, December.

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