This work identifies the loss score as the signal to broadcast, supplies the orthogonality theory and theoretical grounding for the three-factor learning rule from neuroscience, and shows how score vector expansion enriches the decorrelation directions of the resulting objective.
M. Uzun, Mete Erdogan, Cengiz Pehlevan et al.· arXiv.org· 0 citations
Over 10,000 communities of language-model agents that repeatedly exchange messages and revise their opinions across objective mathematics questions and subjective political statements demonstrate that collective behavior of AI agents, like that of other complex systems, follows compact and predictive dynamical laws.
Batu El, J. Paeng, Fatih Dinç et al.· 10 citations· ⚡1
AI agents increasingly operate as part of interacting systems rather than in isolation. As agents exchange information and jointly make decisions, their interactions can improve collective reasoning but may also produce herding, polarization, or amplify shared biases. Understanding and predicting these collective dynam...
Batu El, Jinhee Paeng, Fatih Dinç et al.· 0 citations
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