A Micro-Macro Model of Encounter-Driven Information Diffusion in Robot Swarms
2026-02-24 • Robotics
RoboticsMultiagent Systems
AI summaryⓘ
The authors introduce a new problem called Encounter-Driven Information Diffusion (EDID), where robots can only share information when they physically meet, but they cannot plan these meetings. They develop a two-level model to describe how information spreads in such situations: one at a small scale focusing on individual encounters, and another at a larger scale showing overall diffusion trends. They test their model through various simulations changing factors like swarm size and communication range. The authors also discuss how their model can help design better storage and routing methods for information sharing in robot groups.
Information DiffusionMulti-Robot SystemsSwarm RoboticsMean Free PathRouting AlgorithmsRandom MotionCommunication RangeSimulationMobile RobotsEncounter-Driven Networks
Authors
Davis S. Catherman, Carlo Pinciroli
Abstract
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.