SIGMAS: Second-Order Interaction-based Grouping for Overlapping Multi-Agent Swarms

• URL: http://arxiv.org/abs/2603.00120v1
• Date: Mon, 23 Feb 2026 01:43:56 GMT
• Title: SIGMAS: Second-Order Interaction-based Grouping for Overlapping Multi-Agent Swarms
• Authors: Minah Lee, Saibal Mukhopadhyay,
• Abstract summary: We introduce the novel task of group prediction in overlapping multi-agent swarms.<n>We propose SIGMAS (Second-order Interaction-based Grouping for Multi-Agent Swarms), a self-supervised framework for group inference.<n>We show that SIGMAS accurately recovers latent group structures and remains robust under simultaneously overlapping swarm dynamics.
• Score: 12.265270375417517
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Swarming systems, such as drone fleets and robotic teams, exhibit complex dynamics driven by both individual behaviors and emergent group-level interactions. Unlike traditional multi-agent domains such as pedestrian crowds or traffic systems, swarms typically consist of a few large groups with inherent and persistent memberships, making group identification essential for understanding fine-grained behavior. We introduce the novel task of group prediction in overlapping multi-agent swarms, where latent group structures must be inferred directly from agent trajectories without ground-truth supervision. To address this challenge, we propose SIGMAS (Second-order Interaction-based Grouping for Multi-Agent Swarms), a self-supervised framework that goes beyond direct pairwise interactions and model second-order interaction across agents. By capturing how similarly agents interact with others, SIGMAS enables robust group inference and adaptively balances individual and collective dynamics through a learnable gating mechanism for joint reasoning. Experiments across diverse synthetic swarm scenarios demonstrate that SIGMAS accurately recovers latent group structures and remains robust under simultaneously overlapping swarm dynamics, establishing both a new benchmark task and a principled modeling framework for swarm understanding.

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