Henry Hickson, Sabine Hauert, Alex Mavromatis (2025). "Back to Bee-sics: Learning Information Sharing Strategies for Robot Swarms Through the Hive." Proceedings of the ALIFE 2025: Ciphers of Life: Proceedings of the Artificial Life Conference 2025. Kyoto, Japan. (pp. 78). DOI: 10.1162/ISAL.a.906
Abstract: Effective coordination in multi-robot systems depends on the ability to share useful information. Excessive informationsharing can lead to bandwidth bottlenecks, while insufficient information-sharing limits performance. In this study, we use a learning-based approach to optimise information sharing in a hybrid robot swarm, where each robot maintains local autonomy, but information is shared via a central repository. To do so, we present the Hive, a central mechanism for managing information. We use a genetic algorithm to evolve weights that determine only the minimal information to share for a given task. We validate this approach in a simulated point-to-point logistics task, demonstrating that the Hive significantly reduces communication bandwidth with no loss in performance. Our results show that local decision-making, combined with optimised Hive-based sharing of information, has the potential to lead to adaptable and scalable swarm deployments.
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