ArticleNature human behaviour2023
Scaffolding cooperation in human groups with deep reinforcement learning.
Article in Nature human behaviour, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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Who cites it
9 citing papers in PubMed.
- Propagation and preservation of AI-discovered problem-solving strategies in human culture.Nature communications · 2026Article
- Human 2.0? AI and the Future of Well-Being, Connection, and Personal Growth: A Narrative Review.Behavioral sciences (Basel, Switzerland) · 2026Review
- On the optimal integration of intelligent agents into network systems to steer cooperation.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Decision time is associated with future cooperation and social rewiring decisions in network public goods games.PloS one · 2026Article
- Predicting human cooperation: sensitizing drift-diffusion model to interaction and external stimuli.Journal of the Royal Society, Interface · 2025Article
- Article
- Cooperative bots exhibit nuanced effects on cooperation across strategic frameworks.Journal of the Royal Society, Interface · 2025Article
- Simple autonomous agents can enhance creative semantic discovery by human groups.Nature communications · 2024Article
- Enhancing social cohesion with cooperative bots in societies of greedy, mobile individuals.PNAS nexus · 2024Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.