The Hidden Benefits of Limited Communication and Slow Sensing in Collective Monitoring of Dynamic Environments

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Abstract

Most of our experiences, as well as our intuition, are usually built on a linear understanding of systems and processes. Complex systems in general, and more specifically swarm robotics in this context, leverage non-linear effects to self-organize and to ensure that ‘more is different’. In previous work, the non-linear and therefore counter-intuitive effect of ‘less is more’ was shown for a site-selection swarm scenario. Although it seems intuitive that being able to communicate over longer distances should be beneficial, swarms were found to sometimes profit from communication limitations. Here, we build on this work and show the same effect for the collective perception scenario in a dynamic environment. We also find an additional effect that we call ‘slower is faster’: in certain situations, swarms benefit from sampling their environment less frequently. Our findings are supported by an intensive empirical approach and a mean-field model. All our experimental work is based on simulations using the ARGoS simulator extended with a simulator of the smart environment for the Kilobot robot called Kilogrid.

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APA

Aust, T., Talamali, M. S., Dorigo, M., Hamann, H., & Reina, A. (2022). The Hidden Benefits of Limited Communication and Slow Sensing in Collective Monitoring of Dynamic Environments. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 13491 LNCS, pp. 234–247). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-20176-9_19

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