arXiv AI By Quanyan Zhu

Multiscale Exit-Join Dynamics: Tactical Consensus and Strategic Coalition Formation

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arXiv:2606. 26139v1 Announce Type: cross Abstract: This paper develops a multiscale model of coalition formation in which strategic exit-and-join decisions are coupled with tactical consensus dynamics inside coalitions.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv AI.

arXiv AI
Jun 2

Scaling Behavior of Single LLM-Driven Multi-Agent Systems

arXiv:2606. 00655v1 Announce Type: cross Abstract: The burgeoning field of LLM-based Multi-Agent Systems (MAS) promises to tackle complex tasks through collaborative intelligence, yet fundamental questions regarding their scaling behavior and intrinsic collective dynamics remain underexplored.

By Jialing Li, Zhouhong Gu, Yin Cai, Hongwei Feng
arXiv Machine Learning
Jul 30

Stable and Budget-Feasible Coalition Formation for Clustered Federated Learning: A Hedonic Potential-Game Approach

arXiv:2607. 26788v1 Announce Type: cross Abstract: Clustered federated learning benefits from organizing heterogeneous participants into coalitions that train coalition-specific models, but such clustering is sustainable only if participants prefer their assigned coalition and the required transfers are affordable.

By Cengis Hasan