A Micro-Macro Model of Encounter-Driven Information Diffusion in Robot Swarms

Fuente: arXiv
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Autores principales: Catherman, Davis S., Pinciroli, Carlo
Formato: Preprint
Publicado: 2026
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author Catherman, Davis S.
Pinciroli, Carlo
author_facet Catherman, Davis S.
Pinciroli, Carlo
contents In this paper, we propose the problem of Encounter-Driven Information Diffusion (EDID). In EDID, robots are allowed to exchange information only upon meeting. Crucially, EDID assumes that the robots are not allowed to schedule their meetings. As such, the robots have no means to anticipate when, where, and who they will meet. As a step towards the design of storage and routing algorithms for EDID, in this paper we propose a model of information diffusion that captures the essential dynamics of EDID. The model is derived from first principles and is composed of two levels: a micro model, based on a generalization of the concept of `mean free path'; and a macro model, which captures the global dynamics of information diffusion. We validate the model through extensive robot simulations, in which we consider swarm size, communication range, environment size, and different random motion regimes. We conclude the paper with a discussion of the implications of this model on the algorithms that best support information diffusion according to the parameters of interest.
format Preprint
id arxiv_https___arxiv_org_abs_2602_21148
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle A Micro-Macro Model of Encounter-Driven Information Diffusion in Robot Swarms
Catherman, Davis S.
Pinciroli, Carlo
Robotics
Multiagent Systems
I.2.11; I.2.9
In this paper, we propose the problem of Encounter-Driven Information Diffusion (EDID). In EDID, robots are allowed to exchange information only upon meeting. Crucially, EDID assumes that the robots are not allowed to schedule their meetings. As such, the robots have no means to anticipate when, where, and who they will meet. As a step towards the design of storage and routing algorithms for EDID, in this paper we propose a model of information diffusion that captures the essential dynamics of EDID. The model is derived from first principles and is composed of two levels: a micro model, based on a generalization of the concept of `mean free path'; and a macro model, which captures the global dynamics of information diffusion. We validate the model through extensive robot simulations, in which we consider swarm size, communication range, environment size, and different random motion regimes. We conclude the paper with a discussion of the implications of this model on the algorithms that best support information diffusion according to the parameters of interest.
title A Micro-Macro Model of Encounter-Driven Information Diffusion in Robot Swarms
topic Robotics
Multiagent Systems
I.2.11; I.2.9
url https://arxiv.org/abs/2602.21148