Distributed Omniscient Observers for Multi-Agent Systems: Design and Applications

Fuente: arXiv
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Autori principali: Cao, Ganghui, Yin, Xunyuan
Natura: Preprint
Pubblicazione: 2026
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author Cao, Ganghui
Yin, Xunyuan
author_facet Cao, Ganghui
Yin, Xunyuan
contents This paper proposes distributed omniscient observers for both heterogeneous and homogeneous linear multi-agent systems, such that each agent can correctly estimate the states of all agents. The observer design is based on local input-output information available to each agent, and knowledge of the global communication graph among agents is not necessarily required. The proposed observers can contribute to distributed Nash equilibrium seeking in multi-player games and the emergence of self-organized social behaviors in artificial swarms. Simulation results demonstrate that artificial swarms can emulate animal social behaviors, including sheepdog herding and honeybee dance-based navigation.
format Preprint
id arxiv_https___arxiv_org_abs_2602_07300
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Distributed Omniscient Observers for Multi-Agent Systems: Design and Applications
Cao, Ganghui
Yin, Xunyuan
Systems and Control
This paper proposes distributed omniscient observers for both heterogeneous and homogeneous linear multi-agent systems, such that each agent can correctly estimate the states of all agents. The observer design is based on local input-output information available to each agent, and knowledge of the global communication graph among agents is not necessarily required. The proposed observers can contribute to distributed Nash equilibrium seeking in multi-player games and the emergence of self-organized social behaviors in artificial swarms. Simulation results demonstrate that artificial swarms can emulate animal social behaviors, including sheepdog herding and honeybee dance-based navigation.
title Distributed Omniscient Observers for Multi-Agent Systems: Design and Applications
topic Systems and Control
url https://arxiv.org/abs/2602.07300