Cognition and Networks

Cognitive Representations in Context

Humans rarely live and think in isolation. Rather, they learn and interact with others in increasingly complex social networks. It is therefore of great theoretical and practical importance to understand how an individual’s behavior shapes, and is simultaneously shaped by, the broader social structures in which they operate. I am deeply interested in exploring the interaction of cognitive representations and the environment, and the way this interaction translates into large-scale collective outcomes. I do so by considering different factors such as selective social learning, inductive biases, and population structure (e.g., network topologies, cultural diversity, human-AI groups), and combining them with computational modeling and large networked behavioral experiments. Some of the projects I am excited about in this space include: (i) the cultural evolution of sung melodies in networked communities (Marjieh et al., 2025), (ii) collective creativity in hybrid human-AI populations (Shiiku et al., 2025), and (iii) task allocation in human-human and human-AI teams (Marjieh et al., 2024).

References

2025

  1. singingnets.png
    Characterizing the Interaction of Cultural Evolution Mechanisms in Experimental Social Networks
    Raja Marjieh, Manuel Anglada-Tort, Thomas L Griffiths, and 1 more author
    In Proceedings of the Annual Meeting of the Cognitive Science Society, 2025
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    The Dynamics of Collective Creativity in Human-AI Social Networks
    Shota Shiiku, Raja Marjieh, Manuel Anglada-Tort, and 1 more author
    In Proceedings of the Annual Meeting of the Cognitive Science Society, 2025

2024

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    Task Allocation in Teams as a Multi-Armed Bandit
    Raja Marjieh, Anand Gokhale, Francesco Bullo, and 1 more author
    ACM Proceedings of Collective Intelligence (CI ’24), 2024